Friend, C. M. & Xu, B. Heterogeneous catalysis: a central science for a sustainable future. Acc. Chem. Res. 50, 517–521 (2017).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Astruc, D. Introduction: nanoparticles in catalysis. Chem. Rev. 120, 461–463 (2020).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Mitchell, S., Qin, R., Zheng, N. & Pérez-RamÃrez, J. Nanoscale engineering of catalytic materials for sustainable technologies. Nat. Nanotechnol. 16, 129–139 (2021).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Stamenkovic, V. R. et al. Improved oxygen reduction activity on Pt3Ni(111) via increased surface site availability. Science 315, 493–497 (2007).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Nørskov, J. K. et al. The nature of the active site in heterogeneous metal catalysis. Chem. Soc. Rev. 37, 2163–2171 (2008).ArticleÂ
PubMedÂ
Google ScholarÂ
de Smit, E. et al. Nanoscale chemical imaging of a working catalyst by scanning transmission X-ray microscopy. Nature 456, 222–225 (2008).ArticleÂ
PubMedÂ
Google ScholarÂ
Greeley, J. et al. Alloys of platinum and early transition metals as oxygen reduction electrocatalysts. Nat. Chem. 1, 552–556 (2009).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Strasser, P. et al. Lattice-strain control of the activity in dealloyed core–shell fuel cell catalysts. Nat. Chem. 2, 454–460 (2010).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Lamberti, C., Zecchina, A., Groppo, E. & Bordiga, S. Probing the surfaces of heterogeneous catalysts by in situ IR spectroscopy. Chem. Soc. Rev. 39, 4951–5001 (2010).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Chen, C. et al. Highly crystalline multimetallic nanoframes with three-dimensional electrocatalytic surfaces. Science 343, 1339–1343 (2014).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Calle-Vallejo, F. et al. Finding optimal surface sites on heterogeneous catalysts by counting nearest neighbors. Science 350, 185–189 (2015).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Zhang, L. et al. Platinum-based nanocages with subnanometer-thick walls and well-defined, controllable facets. Science 349, 412–416 (2015).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Escudero-Escribano, M. et al. Tuning the activity of Pt alloy electrocatalysts by means of the lanthanide contraction. Science 352, 73–76 (2016).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Kulkarni, A., Siahrostami, S., Patel, A. & Nørskov, J. K. Understanding catalytic activity trends in the oxygen reduction reaction. Chem. Rev. 118, 2302–2312 (2018).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Núñez, M., Lansford, J. L. & Vlachos, D. G. Optimization of the facet structure of transition-metal catalysts applied to the oxygen reduction reaction. Nat. Chem. 11, 449–456 (2019).ArticleÂ
PubMedÂ
Google ScholarÂ
Wang, L. et al. Tunable intrinsic strain in two-dimensional transition metal electrocatalysts. Science 363, 870–874 (2019).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Kim, S. et al. Correlating 3D surface atomic structure and catalytic activities of Pt nanocrystals. Nano Lett. 21, 1175–1183 (2021).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Lee, J., Jeong, C., Lee, T., Ryu, S. & Yang, Y. Direct observation of three-dimensional atomic structure of twinned metallic nanoparticles and their catalytic properties. Nano Lett. 22, 665–672 (2022).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Kluge, R. M. et al. A trade-off between ligand and strain effects optimizes the oxygen reduction activity of Pt alloys. Energy Environ. Sci. 15, 5181–5191 (2022).ArticleÂ
CASÂ
Google ScholarÂ
Li, M. et al. Ultrafine jagged platinum nanowires enable ultrahigh mass activity for the oxygen reduction reaction. Science 354, 1414–1419 (2016).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Tao, F. et al. Reaction-driven restructuring of Rh–Pd and Pt–Pd core–shell nanoparticles. Science 322, 932–934 (2008).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Cui, C., Gan, L., Heggen, M., Rudi, S. & Strasser, P. Compositional segregation in shaped Pt alloy nanoparticles and their structural behaviour during electrocatalysis. Nat. Mater. 12, 765–771 (2013).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Zugic, B. et al. Dynamic restructuring drives catalytic activity on nanoporous gold–silver alloy catalysts. Nat. Mater. 16, 558–564 (2017).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Jacobse, L., Huang, Y.-F., Koper, M. T. M. & Rost, M. J. Correlation of surface site formation to nanoisland growth in the electrochemical roughening of Pt(111). Nat. Mater. 17, 277–282 (2018).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Timoshenko, J. & Roldan Cuenya, B. In situ/operando electrocatalyst characterization by X-ray absorption spectroscopy. Chem. Rev. 121, 882–961 (2021).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Loukrakpam, R. et al. Nanoengineered PtCo and PtNi catalysts for oxygen reduction reaction: an assessment of the structural and electrocatalytic properties. J. Phys. Chem. C 115, 1682–1694 (2011).ArticleÂ
CASÂ
Google ScholarÂ
De Jonge, N. & Ross, F. M. Electron microscopy of specimens in liquid. Nat. Nanotechnol. 6, 695–704 (2011).ArticleÂ
PubMedÂ
Google ScholarÂ
Wu, J. et al. In situ environmental TEM in imaging gas and liquid phase chemical reactions for materials research. Adv. Mater. 28, 9686–9712 (2016).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Tian, N., Zhou, Z.-Y., Sun, S.-G., Ding, Y. & Wang, Z. L. Synthesis of tetrahexahedral platinum nanocrystals with high-index facets and high electro-oxidation activity. Science 316, 732–735 (2007).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Chattot, R. et al. Surface distortion as a unifying concept and descriptor in oxygen reduction reaction electrocatalysis. Nat. Mater. 17, 827–833 (2018).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Tian, X. et al. Engineering bunched Pt–Ni alloy nanocages for efficient oxygen reduction in practical fuel cells. Science 366, 850–856 (2019).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Miao, J., Ercius, P. & Billinge, S. J. Atomic electron tomography: 3D structures without crystals. Science 353, aaf2157 (2016).ArticleÂ
PubMedÂ
Google ScholarÂ
Scott, M. C. et al. Electron tomography at 2.4-Ã¥ngström resolution. Nature 483, 444–447 (2012).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Zhou, J. et al. Observing crystal nucleation in four dimensions using atomic electron tomography. Nature 570, 500–503 (2019).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Yang, Y. et al. Determining the three-dimensional atomic structure of an amorphous solid. Nature 592, 60–64 (2021).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Moniri, S. et al. Three-dimensional atomic structure and local chemical order of medium- and high-entropy nanoalloys. Nature 624, 564–569 (2023).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Debe, M. K. Electrocatalyst approaches and challenges for automotive fuel cells. Nature 486, 43–51 (2012).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Banham, D. & Ye, S. Current status and future development of catalyst materials and catalyst layers for proton exchange membrane fuel cells: an industrial perspective. ACS Energy Lett. 2, 629–638 (2017).ArticleÂ
CASÂ
Google ScholarÂ
Huang, X. et al. High-performance transition metal-doped Pt3Ni octahedra for oxygen reduction reaction. Science 348, 1230–1234 (2015).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Jia, Q. et al. Roles of Mo surface dopants in enhancing the ORR performance of octahedral PtNi nanoparticles. Nano Lett. 18, 798–804 (2018).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Dionigi, F. et al. Controlling near-surface Ni composition in octahedral PtNi(Mo) nanoparticles by Mo doping for a highly active oxygen reduction reaction catalyst. Nano Lett. 19, 6876–6885 (2019).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Polani, S. et al. Size and composition dependence of oxygen reduction reaction catalytic activities of Mo-doped PtNi/C octahedral nanocrystals. ACS Catal. 11, 11407–11415 (2021).ArticleÂ
CASÂ
Google ScholarÂ
Tran, K. & Ulissi, Z. W. Active learning across intermetallics to guide discovery of electrocatalysts for CO2 reduction and H2 evolution. Nat. Catal. 1, 696–703 (2018).ArticleÂ
CASÂ
Google ScholarÂ
Zhong, M. et al. Accelerated discovery of CO2 electrocatalysts using active machine learning. Nature 581, 178–183 (2020).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Nørskov, J. K. et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B 108, 17886–17892 (2004).ArticleÂ
Google ScholarÂ
Nanba, Y. & Koyama, M. An element-based generalized coordination number for predicting the oxygen binding energy on Pt3M (M = Co, Ni, or Cu) alloy nanoparticles. ACS Omega 6, 3218–3226 (2021).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Calle-Vallejo, F. & Bandarenka, A. S. Enabling generalized coordination numbers to describe strain effects. ChemSusChem 11, 1824–1828 (2018).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Wang, C. et al. Correlation between surface chemistry and electrocatalytic properties of monodisperse PtxNi1−x nanoparticles. Adv. Funct. Mater. 21, 147–152 (2011).ArticleÂ
Google ScholarÂ
Lee, J. D. et al. Tuning the electrocatalytic oxygen reduction reaction activity of Pt–Co nanocrystals by cobalt concentration with atomic-scale understanding. ACS Appl. Mater. Interfaces 11, 26789–26797 (2019).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Shinozaki, K., Zack, J. W., Richards, R. M., Pivovar, B. S. & Kocha, S. S. Oxygen reduction reaction measurements on platinum electrocatalysts utilizing rotating disk electrode technique. J. Electrochem. Soc. 162, F1144–F1158 (2015).ArticleÂ
CASÂ
Google ScholarÂ
Dabov, K., Foi, A., Katkovnik, V. & Egiazarian, K. Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Trans. Image Process. 16, 2080–2095 (2007).ArticleÂ
PubMedÂ
Google ScholarÂ
Yang, Y. et al. Deciphering chemical order/disorder and material properties at the single-atom level. Nature 542, 75–79 (2017).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Chen, C.-C. et al. Three-dimensional imaging of dislocations in a nanoparticle at atomic resolution. Nature 496, 74–77 (2013).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Otsu, N. A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man. Cybern. 9, 62–66 (1979).ArticleÂ
Google ScholarÂ
Pham, M., Yuan, Y., Rana, A., Osher, S. & Miao, J. Accurate real space iterative reconstruction (RESIRE) algorithm for tomography. Sci. Rep. 13, 5624 (2023).ArticleÂ
CASÂ
PubMedÂ
PubMed CentralÂ
Google ScholarÂ
Jia, Q. et al. Activity descriptor identification for oxygen reduction on platinum-based bimetallic nanoparticles: in situ observation of the linear composition–strain–activity relationship. ACS Nano 9, 387–400 (2015).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Newville, M. IFEFFIT: interactive XAFS analysis and FEFF fitting. J. Synchrotron Radiat. 8, 322–324 (2001).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Ravel, B. & Gallagher, K. Atomic structure and the magnetic properties of Zr-doped Sm2Co17. Phys. Scr. 2005, 606 (2005).ArticleÂ
Google ScholarÂ
Newville, M., LÄ«viņš, P., Yacoby, Y., Rehr, J. J. & Stern, E. A. Near-edge x-ray-absorption fine structure of Pb: a comparison of theory and experiment. Phys. Rev. B 47, 14126–14131 (1993).ArticleÂ
CASÂ
Google ScholarÂ
Ankudinov, A. L., Ravel, B., Rehr, J. J. & Conradson, S. D. Real-space multiple-scattering calculation and interpretation of x-ray-absorption near-edge structure. Phys. Rev. B 58, 7565–7576 (1998).ArticleÂ
CASÂ
Google ScholarÂ
Do Carmo, M. P. Differential Geometry of Curves and Surfaces 2nd edn (Dover Publications, 2016).Lechner, W. & Dellago, C. Accurate determination of crystal structures based on averaged local bond order parameters. J. Chem. Phys. 129, 114707 (2008).ArticleÂ
PubMedÂ
Google ScholarÂ
Li, Q.-J., Sheng, H. & Ma, E. Strengthening in multi-principal element alloys with local-chemical-order roughened dislocation pathways. Nat. Commun. 10, 3563 (2019).ArticleÂ
PubMedÂ
Google ScholarÂ
Mortensen, J. J. et al. GPAW: an open Python package for electronic structure calculations. J. Chem. Phys. 160, 092503 (2024).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Larsen, A. H. et al. J. Condens. Matter Phys. 29, 273002 (2017).Kresse, G. & Hafner, J. Ab initio molecular dynamics for liquid metals. Phys. Rev. B 47, 558–561 (1993).ArticleÂ
CASÂ
Google ScholarÂ
Kresse, G. & Hafner, J. Ab initio molecular-dynamics simulation of the liquid-metal–amorphous-semiconductor transition in germanium. Phys. Rev. B 49, 14251–14269 (1994).ArticleÂ
CASÂ
Google ScholarÂ
Kresse, G. & Furthmüller, J. Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Phys. Rev. B 54, 11169–11186 (1996).ArticleÂ
CASÂ
Google ScholarÂ
Kresse, G. & Furthmüller, J. Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Comput. Mater. Sci. 6, 15–50 (1996).ArticleÂ
CASÂ
Google ScholarÂ
Mortensen, J. J., Hansen, L. B. & Jacobsen, K. W. Real-space grid implementation of the projector augmented wave method. Phys. Rev. B 71, 035109 (2005).ArticleÂ
Google ScholarÂ
Enkovaara, J. et al. Electronic structure calculations with GPAW: a real-space implementation of the projector augmented-wave method. J. Phys. Condens. Matter 22, 253202 (2010).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Kresse, G. & Joubert, D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B 59, 1758–1775 (1999).ArticleÂ
CASÂ
Google ScholarÂ
Perdew, J. P., Burke, K. & Ernzerhof, M. Generalized gradient approximation made simple. Phys. Rev. Lett. 77, 3865–3868 (1996).ArticleÂ
CASÂ
PubMedÂ
Google ScholarÂ
Rasmussen, C. E. in Advanced Lectures on Machine Learning (eds Bousquet, O. et al.) 63–71 (Springer, 2003).Himanen, L. et al. DScribe: library of descriptors for machine learning in materials science. Comput. Phys. Commun. 247, 106949 (2020).ArticleÂ
CASÂ
Google ScholarÂ
Bartók, A. P., Kondor, R. & Csányi, G. On representing chemical environments. Phys. Rev. B 87, 184115 (2013).ArticleÂ
Google ScholarÂ
Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
Google ScholarÂ
Viswanathan, V., Hansen, H. A., Rossmeisl, J. & Nørskov, J. K. Universality in oxygen reduction electrocatalysis on metal surfaces. ACS Catal. 2, 1654–1660 (2012).ArticleÂ
CASÂ
Google ScholarÂ