The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Non-equilibrium restructurings in catalysis: A chemical space odyssey
Open accessPublished version of a preprint
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Scaling deep learning for materials discovery
Merchant, A., Batzner, S., Schoenholz, S. S., Aykol, M., Cheon, G., & Cubuk, E. D. (2023) · Nature · doi:10.1038/s41586-023-06735-9 · Cited by 1,527
Markov state models of biomolecular conformational dynamics
Chodera, J. D., & Noé, F. (2014) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2014.04.002 · Cited by 776
Wan, C., Zhang, Z., Dong, J., Xu, M., Pu, H., Baumann, D., Lin, Z., Wang, S., Huang, J., Shah, A. H., et al. (2023) · Nature Materials · doi:10.1038/s41563-023-01584-3 · Cited by 404
Self-citation
Research works printed but not linked: 98
- T. Lee, A. Soon, The rise of ab initio surface thermodynamics. Nat. Catal. 7(1), 4–6 (2024). https://doi.org/10.1038/s41929-023-01088-y · DOI
- Z.W. Seh, J. Kibsgaard, C.F. Dickens, I. Chorkendorff, J.K. Nørskov, T.F. Jaramillo, Combining theory and experiment in electrocatalysis: insights into materials design. Science 355(6321), 4998 (2017). https://doi.org/10.1126/science.aad4998 · DOI · Paper page
- H. Zhang, L. Chen, F. Dong, Z. Lu, E. Lv, X. Dong, H. Li, Z. Yuan, X. Peng, S. Yang, J. Qiu, Z. Guo, Z. Wen, Dynamic transformation of active sites in energy and environmental catalysis. Energy Environ. Sci. 17(18), 6435–6481 (2024). https://doi.org/10.1039/D4EE02365J · DOI
- H. Xin, A. Vojvodic, J. Voss, J.K. Nørskov, F. Abild-Pedersen, Effects of d -band shape on the surface reactivity of transition-metal alloys. Phys. Rev. B 89(11), 115114–115118 (2014). https://doi.org/10.1103/PhysRevB.89.115114 · DOI
- Z. Zhang, B. Zandkarimi, J. Munarriz, C.E. Dickerson, A.N. Alexandrova, Fluxionality of subnano clusters reshapes the activity volcano of electrocatalysis. ChemCatChem 14(15), 202200345–202200345 (2022). https://doi.org/10.1002/cctc.202200345 · DOI
- Z. Zhang, Z. Wei, P. Sautet, A.N. Alexandrova, Hydrogen-induced restructuring of a Cu(100) electrode in electroreduction conditions. J. Am. Chem. Soc. 144(42), 19284–19293 (2022). https://doi.org/10.1021/jacs.2c06188 · DOI
- D. Cheng, Z. Wei, Z. Zhang, P. Broekmann, A.N. Alexandrova, P. Sautet, Restructuring and activation of Cu(111) under electrocatalytic reduction conditions. Angew. Chem. Int. Ed. 62(20), 202218575–202218575 (2023). https://doi.org/10.1002/anie.202218575 · DOI
- Z. Zhang, E. Jimenez-Izal, I. Hermans, A.N. Alexandrova, Dynamic phase diagram of catalytic surface of hexagonal boron nitride under conditions of oxidative dehydrogenation of propane. J. Phys. Chem. Lett. 10(1), 20–25 (2019). https://doi.org/10.1021/acs.jpclett.8b03373 · DOI
- Z. Zhang, I. Hermans, A.N. Alexandrova, Off-stoichiometric restructuring and sliding dynamics of hexagonal boron nitride edges in conditions of oxidative dehydrogenation of propane. J. Am. Chem. Soc. 145(31), 17265–17273 (2023). https://doi.org/10.1021/jacs.3c04613 · DOI
- Z. Zhang, T. Masubuchi, P. Sautet, S.L. Anderson, A.N. Alexandrova, Hydrogen evolution on electrode-supported Ptn clusters: ensemble of hydride states governs the size dependent reactivity. Angew. Chem. Int. Ed. 62(20), 202218210–202218210 (2023). https://doi.org/10.1002/anie.202218210 · DOI
- Z. Zhang, B. Zandkarimi, A.N. Alexandrova, Ensembles of metastable states govern heterogeneous catalysis on dynamic interfaces. Acc. Chem. Res. 53(2), 447–458 (2020). https://doi.org/10.1021/acs.accounts.9b00531 · DOI
- R.H. Lavroff, H.W.T. Morgan, Z. Zhang, P. Poths, A.N. Alexandrova, Ensemble representation of catalytic interfaces: soloists, orchestras, and everything in-between. Chem. Sci. 13(27), 8003–8016 (2022). https://doi.org/10.1039/d2sc01367c · DOI
- K. Reuter, M. Scheffler, First-principles atomistic thermodynamics for oxidation catalysis: surface phase diagrams and catalytically interesting regions. Phys. Rev. Lett. 90(4), 046103 (2003). https://doi.org/10.1103/PhysRevLett.90.046103 · DOI
- A.V. Marenich, A. Majumdar, M. Lenz, C.J. Cramer, D.G. Truhlar, Construction of Pourbaix diagrams for ruthenium-based water-oxidation catalysts by density functional theory. Angew. Chem. Int. Ed. 51(51), 12810–12814 (2012). https://doi.org/10.1002/anie.201206012 · DOI
- M.K. Horton, P. Huck, R.X. Yang, J.M. Munro, S. Dwaraknath, A.M. Ganose, R.S. Kingsbury, M. Wen, J.X. Shen, T.S. Mathis, A.D. Kaplan, K. Berket, J. Riebesell, J. George, A.S. Rosen, E.W.C. Spotte-Smith, M.J. McDermott, O.A. Cohen, A. Dunn, M.C. Kuner, G.-M. Rignanese, G. Petretto, D. Waroquiers, S.M. Griffin, J.B. Neaton, D.C. Chrzan, M. Asta, G. Hautier, S. Cholia, G. Ceder, S.P. Ong, A. Jain, K.A. Persson, Accelerated data-driven materials science with the Materials Project. Nat. Mater. (2025). https://doi.org/10.1038/s41563-025-02272-0 · DOI
- R.B. Wexler, T. Qiu, A.M. Rappe, Automatic prediction of surface phase diagrams using ab initio grand canonical Monte Carlo. J. Phys. Chem. C 123(4), 2321–2328 (2019). https://doi.org/10.1021/acs.jpcc.8b11093 · DOI
- G. Sun, A.N. Alexandrova, P. Sautet, Pt8 cluster on alumina under a pressure of hydrogen: support-dependent reconstruction from first-principles global optimization. J. Chem. Phys. 151(19), 194703–194703 (2019). https://doi.org/10.1063/1.5129296 · DOI
- Z. Zhang, W. Gee, R.H. Lavroff, A.N. Alexandrova, GOCIA: a grand canonical global optimizer for clusters, interfaces, and adsorbates. Phys. Chem. Chem. Phys. 27(2), 696–706 (2025). https://doi.org/10.1039/D4CP03801K · DOI
- J.M. Venegas, Z. Zhang, T.O. Agbi, W.P. McDermott, A. Alexandrova, I. Hermans, Why boron nitride is such a selective catalyst for the oxidative dehydrogenation of propane. Angew. Chem. Int. Ed. 59(38), 16527–16535 (2020). https://doi.org/10.1002/anie.202003695 · DOI
- X. Qi, Z. Chen, T. Yan, K.A. Fichthorn, Growth mechanism of five-fold twinned Ag nanowires from multiscale theory and simulations. ACS Nano 13(4), 4647–4656 (2019). https://doi.org/10.1021/acsnano.9b00820 · DOI
- Y. Xia, Y. Xiong, B. Lim, S.E. Skrabalak, Shape-controlled synthesis of metal nanocrystals: simple chemistry meets complex physics? Angew. Chem. Int. Ed. 48(1), 60–103 (2009). https://doi.org/10.1002/anie.200802248 · DOI · Paper page
- C.-T. Chen, A. Sviripa, S. Verma, C. Paolucci, D.W. Flaherty, Reactions of surface peroxides contribute to rates and selectivities for C2H4 epoxidation on silver. ACS Catal. 15(2), 1387–1398 (2025). https://doi.org/10.1021/acscatal.4c06945 · DOI
- P. Poths, K.C. Lai, F. Cannizzaro, C. Scheurer, S. Matera, K. Reuter, ML-accelerated automatic process exploration reveals facile O-induced Pd step-edge restructuring on catalytic time scales. ACS Catal. 15(1), 514–522 (2025). https://doi.org/10.1021/acscatal.4c06414 · DOI
- H. Matsushima, A. Taranovskyy, C. Haak, Y. Gründer, O.M. Magnussen, Reconstruction of Cu(100) electrode surfaces during hydrogen evolution. J. Am. Chem. Soc. 131(30), 10362–10363 (2009). https://doi.org/10.1021/ja904033t · DOI
- Z. Zhang, W. Gee, P. Sautet, A.N. Alexandrova, H and CO co-induced roughening of Cu surface in CO2 electroreduction conditions. J. Am. Chem. Soc. 146(23), 16119–16127 (2024). https://doi.org/10.1021/jacs.4c03515 · DOI
- J. Wei, Z. Zhang, W. Gee, Y. Wei, Y.-W. Zhou, M. Herran, P. Sautet, A.N. Alexandrova, B. Roldan Cuenya, C.S. Kley, Role of surface hydroxyls in atomic-scale copper restructuring during CO electroreduction. J. Am. Chem. Soc. (2025). https://doi.org/10.1021/jacs.5c14516 · DOI
- B. Zandkarimi, P. Poths, A.N. Alexandrova, When fluxionality beats size selection: acceleration of Ostwald ripening of sub-nano clusters. Angew. Chem. Int. Ed. 60(21), 11973–11982 (2021). https://doi.org/10.1002/anie.202100107 · DOI
- B. Zhu, S. Chen, Y. Jiang, H. Zhang, R. Qi, Y. Han, Z. Liu, B. Yang, M. Hiroaki, C. Zeng, W. Yuan, H. Yang, Z. Zhang, J. Hu, Y. Wang, Y. Gao, Non-negligible entropy effect on sintering of supported nanoparticles. arXiv (2022). https://doi.org/10.48550/arXiv.2204.00812 · DOI
- T. Wang, J. Hu, R. Ouyang, Y. Wang, Y. Huang, S. Hu, W.-X. Li, Nature of metal-support interaction for metal catalysts on oxide supports. Science 386(6724), 915–920 (2024). https://doi.org/10.1126/science.adp6034 · DOI
- G. Sun, P. Sautet, Active site fluxional restructuring as a new paradigm in triggering reaction activity for nanocluster catalysis. Acc. Chem. Res. 54(20), 3841–3849 (2021). https://doi.org/10.1021/acs.accounts.1c00413 · DOI
- Z. Zhang, F. Abild-Pedersen, Off-equilibrium reactivity of boron-enriched metal diboride surfaces in electroreduction conditions. ACS Catal. (2025). https://doi.org/10.1021/acscatal.5c04054 · DOI
- H. Zhai, A.N. Alexandrova, Local fluxionality of surface-deposited cluster catalysts: the case of pt7 on Al2O3. J. Phys. Chem. Lett. 9(7), 1696–1702 (2018). https://doi.org/10.1021/acs.jpclett.8b00379 · DOI
- P. Poths, S. Vargas, P. Sautet, A.N. Alexandrova, Thermodynamic equilibrium versus kinetic trapping: thermalization of cluster catalyst ensembles can extend beyond reaction time scales. ACS Catal. 14(7), 5403–5415 (2024). https://doi.org/10.1021/acscatal.3c06154 · DOI
- D. Cheng, K.-L.C. Nguyen, V. Sumaria, Z. Wei, Z. Zhang, W. Gee, Y. Li, C.G. Morales-Guio, M. Heyde, B. Roldan Cuenya, A.N. Alexandrova, P. Sautet, Structure sensitivity and catalyst restructuring for CO2 electro-reduction on copper. Nat. Commun. 16(1), 4064 (2025). https://doi.org/10.1038/s41467-025-59267-3 · DOI
- R. Lipin, M. Vandichel, Modeling metal electrocatalysts as cathodes: the urgent need to look beneath the surface. ACS Energy Lett. 10(11), 5880–5884 (2025). https://doi.org/10.1021/acsenergylett.5c02339 · DOI
- R. Amirbeigiarab, J. Tian, A. Herzog, C. Qiu, A. Bergmann, B. Roldan Cuenya, O.M. Magnussen, Atomic-scale surface restructuring of copper electrodes under CO2 electroreduction conditions. Nat. Catal. 6(9), 837–846 (2023). https://doi.org/10.1038/s41929-023-01009-z · DOI
- Z. Wu, L. Huang, H. Liu, M. Li, H. Wang, Surface oxidation of transition metal sulfide and phosphide nanomaterials. Nano Res. 14(7), 2264–2267 (2021). https://doi.org/10.1007/s12274-020-3219-5 · DOI
- X. Bai, X. Zhao, Y. Zhang, C. Ling, Y. Zhou, J. Wang, Y. Liu, Dynamic stability of copper single-atom catalysts under working conditions. J. Am. Chem. Soc. 144(37), 17140–17148 (2022). https://doi.org/10.1021/jacs.2c07178 · DOI
- A.H. Shah, Z. Zhang, Z. Huang, S. Wang, G. Zhong, C. Wan, A.N. Alexandrova, Y. Huang, X. Duan, The role of alkali metal cations and platinum-surface hydroxyl in the alkaline hydrogen evolution reaction. Nat. Catal. 5(10), 923–933 (2022). https://doi.org/10.1038/s41929-022-00851-x · DOI · Paper page
- D. Raciti, T.P. Moffat, Hydride formation and decomposition on Cu(111) in HClO4. J. Am. Chem. Soc. 147(5), 4038–4051 (2025). https://doi.org/10.1021/jacs.4c12782 · DOI
- D. Raciti, E. Cockayne, J. Vinson, K. Schwarz, A.R. Hight Walker, T.P. Moffat, Shiners study of chloride order-disorder phase transition and solvation of Cu(100). J. Am. Chem. Soc. 146(2), 1588–1602 (2024). https://doi.org/10.1021/jacs.3c11812 · DOI
- Z. He, M. Ajmal, M. Zhang, X. Liu, Z.-F. Huang, C. Shi, R. Gao, L. Pan, X. Zhang, J.-J. Zou, Progress in manipulating dynamic surface reconstruction via anion modulation for electrocatalytic water oxidation. Adv. Sci. 10(29), 2304071 (2023). https://doi.org/10.1002/advs.202304071 · DOI
- S. Ma, K. Wang, M. Rafique, J. Han, Q. Fu, S. Jiang, X. Wang, T. Yao, P. Xu, B. Song, Reconstruction of ferromagnetic/paramagnetic cobalt-based electrocatalysts under gradient magnetic fields for enhanced oxygen evolution. Angew. Chem. Int. Ed. 63(46), 202412821 (2024). https://doi.org/10.1002/anie.202412821 · DOI
- H. Guo, P. Sautet, A.N. Alexandrova, Reagent-triggered isomerization of fluxional cluster catalyst via dynamic coupling. J. Phys. Chem. Lett. 11(8), 3089–3094 (2020). https://doi.org/10.1021/acs.jpclett.0c00548 · DOI
- L. Wu, Z. Wu, F. Li, Z. Wang, Z. Zhang, X.-Q. Gong, W. Huang, Surface reconstruction-induced photocatalytic methanol reduction reaction on a rutile TiO2(001) surface. J. Phys. Chem. Lett. 15(33), 8481–8486 (2024). https://doi.org/10.1021/acs.jpclett.4c02137 · DOI
- Y. Xia, P. Sautet, Plasma oxidation of copper: molecular dynamics study with neural network potentials. ACS Nano 16(12), 20680–20692 (2022). https://doi.org/10.1021/acsnano.2c07712 · DOI
- A.N. Alexandrova, P. Christopher, Heterogeneous catalysis: optimal performance at a phase boundary? Matter (2025). https://doi.org/10.1016/j.matt.2025.102209 · DOI
- T. Gong, G. Qiu, M.-R. He, O.V. Safonova, W.-C. Yang, D. Raciti, C. Oses, A.S. Hall, Atomic ordering-induced ensemble variation in alloys governs electrocatalyst on/off states. J. Am. Chem. Soc. 147(1), 510–518 (2025). https://doi.org/10.1021/jacs.4c11753 · DOI
- B. Werghi, S. Saini, P.-H. Chung, A. Kumar, A.M. Ebrahim, K. Abels, M. Chi, F. Abild-Pedersen, S.R. Bare, M. Cargnello, Dynamic behavior of Pt multimetallic alloys for active and stable propane dehydrogenation catalysts. J. Am. Chem. Soc. 146(45), 30966–30975 (2024). https://doi.org/10.1021/jacs.4c09424 · DOI
- B. Zandkarimi, T.J. Gorey, G. Li, J. Munarriz, S.L. Anderson, A.N. Alexandrova, Alloying with Sn suppresses sintering of size-selected subnano Pt clusters on SiO2with and without adsorbates. Chem. Mater. 32(19), 8595–8605 (2020). https://doi.org/10.1021/acs.chemmater.0c02926 · DOI
- P. Poths, G. Li, T. Masubuchi, H.W.T. Morgan, Z. Zhang, A.N. Alexandrova, S.L. Anderson, Got coke? Self-limiting poisoning makes an ultra stable and selective sub-nano cluster catalyst. ACS Catal. 13(2), 1533–1544 (2023). https://doi.org/10.1021/acscatal.2c05634 · DOI
- Z. Duan, G. Henkelman, Atomic-scale mechanisms of electrochemical Pt dissolution. ACS Catal. 11(23), 14439–14447 (2021). https://doi.org/10.1021/acscatal.1c02366 · DOI
- J. Choi, S. Chiu, A. Banerjee, R.L. Sacci, G.M. Veith, C. Stieber, C. Hahn, A.N. Alexandrova, C.G. Morales-Guio, Corrosion and enhanced hydrogen evolution in electrochemical reduction of ammonium carbamate on transition metal surfaces. J. Phys. Chem. Lett. 15(31), 8007–8017 (2024). https://doi.org/10.1021/acs.jpclett.4c01638 · DOI
- P. Hou, Q. Yu, F. Luo, J.-C. Liu, Reactant-induced dynamic active sites on Cu catalysts during the water-gas shift reaction. ACS Catal. 15(1), 352–360 (2025). https://doi.org/10.1021/acscatal.4c05338 · DOI
- Y. Yang, J. Feijóo, M. Figueras-Valls, C. Chen, C. Shi, M.V. Fonseca Guzman, Y. Murhabazi Maombi, S. Liu, P. Jain, V. Briega-Martos, Z. Peng, Y. Shan, G. Lee, M. Rebarchik, L. Xu, C.J. Pollock, J. Jin, N.E. Soland, C. Wang, M.B. Salmeron, Z. Chen, Y. Han, M. Mavrikakis, P. Yang, Operando probing dynamic migration of copper carbonyl during electrocatalytic CO2 reduction. Nat. Catal. 8(6), 579–594 (2025). https://doi.org/10.1038/s41929-025-01359-w · DOI
- D.M. Harraz, K.M. Lodaya, B.Y. Tang, Y. Surendranath, Homogeneous-heterogeneous bifunctionality in Pd-catalyzed vinyl acetate synthesis. Science 388(6742), 7913 (2025). https://doi.org/10.1126/science.ads7913 · DOI
- S. Wei, A. Li, J.-C. Liu, Z. Li, W. Chen, Y. Gong, Q. Zhang, W.-C. Cheong, Y. Wang, L. Zheng, Direct observation of noble metal nanoparticles transforming to thermally stable single atoms. Nat. Nanotechnol. 13(9), 856–861 (2018) · DOI
- S. Zhang, Y. Han, X.-Y. Li, Q. Tang, B. Zhu, Y. Gao, Particle hopping and coalescence of supported Au nanoparticles in harsh reactive environments. J. Am. Chem. Soc. 147(18), 15796–15805 (2025). https://doi.org/10.1021/jacs.5c03633 · DOI
- H. Frey, A. Beck, X. Huang, J.A. van Bokhoven, M.-G. Willinger, Dynamic interplay between metal nanoparticles and oxide support under redox conditions. Science 376(6596), 982–987 (2022) · DOI
- N. Daelman, M. Capdevila-Cortada, N. López, Dynamic charge and oxidation state of Pt/CeO2 single-atom catalysts. Nat. Mater. 18(11), 1215–1221 (2019). https://doi.org/10.1038/s41563-019-0444-y · DOI
- R.M. Arán-Ais, F. Scholten, S. Kunze, R. Rizo, B. Roldan Cuenya, The role of in situ generated morphological motifs and Cu(i) species in C2+ product selectivity during CO2 pulsed electroreduction. Nat. Energy 5(4), 317–325 (2020). https://doi.org/10.1038/s41560-020-0594-9 · DOI
- M. Schmid, G.S. Parkinson, U. Diebold, Analysis of temperature-programmed desorption via equilibrium thermodynamics. ACS Phys. Chem. Au 3(1), 44–62 (2023). https://doi.org/10.1021/acsphyschemau.2c00031 · DOI
- G. Sun, J.T. Fuller, A.N. Alexandrova, P. Sautet, Global activity search uncovers reaction induced concomitant catalyst restructuring for alkane dissociation on model Pt catalysts. ACS Catal. 11(3), 1877–1885 (2021). https://doi.org/10.1021/acscatal.0c05421 · DOI
- Y. Liu, A. Madanchi, A.S. Anker, L. Simine, V.L. Deringer, The amorphous state as a frontier in computational materials design. Nat. Rev. Mater. 10(3), 228–241 (2025). https://doi.org/10.1038/s41578-024-00754-2 · DOI
- Z. Weng, X. Zhang, Y. Wu, S. Huo, J. Jiang, W. Liu, G. He, Y. Liang, H. Wang, Self-cleaning catalyst electrodes for stabilized CO2 reduction to hydrocarbons. Angew. Chem. Int. Ed. 56(42), 13135–13139 (2017). https://doi.org/10.1002/anie.201707478 · DOI
- P. Jangid, S. Chaudhury, A. Kolomeisky, Theoretical understanding of dynamic catalysis. J. Phys. Chem. C 128(22), 9077–9089 (2024). https://doi.org/10.1021/acs.jpcc.4c02713 · DOI
- S. Jung, C. Pizzolitto, P. Biasi, P.J. Dauenhauer, T. Birol, Programmable catalysis by support polarization: elucidating and breaking scaling relations. Nat. Commun. 14(1), 7795 (2023). https://doi.org/10.1038/s41467-023-43641-0 · DOI
- R. Chen, S. Neri, L.J. Prins, Enhanced catalytic activity under non-equilibrium conditions. Nat. Nanotechnol. 15(10), 868–874 (2020) · DOI
- M.A. Ardagh, M. Shetty, A. Kuznetsov, Q. Zhang, P. Christopher, D.G. Vlachos, O.A. Abdelrahman, P.J. Dauenhauer, Catalytic resonance theory: parallel reaction pathway control. Chem. Sci. 11(13), 3501–3510 (2020). https://doi.org/10.1039/C9SC06140A · DOI
- J.G. Vitillo, C.J. Cramer, L. Gagliardi, Multireference methods are realistic and useful tools for modeling catalysis. Isr. J. Chem. 62(1–2), 202100136–202100136 (2022)
- R. Fanta, M. Bajdich, Resolution of selectivity steps of CO reduction reaction on copper by quantum Monte Carlo. J. Phys. Chem. Lett. 16(6), 1494–1500 (2025). https://doi.org/10.1021/acs.jpclett.4c03409 · DOI
- I. Aprahamian, S.M. Goldup, Non-equilibrium steady states in catalysis, molecular motors, and supramolecular materials: why networks and language matter. J. Am. Chem. Soc. 145(26), 14169–14183 (2023) · DOI
- X. Fang, K. Kruse, T. Lu, J. Wang, Nonequilibrium physics in biology. Rev. Mod. Phys. 91(4), 045004 (2019) · DOI
- S. Gavrilets, Fitness Landscapes and the Origin of Species, vol. 41 (Princeton University Press, Princeton, 2018) · DOI
- A. Moreau, D.T. Nguyen, A.J. Hinbest, A. Zamora, R. Weerasekera, K. Matej, X. Zhou, S. Sanchez, I. Rodriguez Brenes, J.-S.B. Tai, Surface remodeling and inversion of cell-matrix interactions underlie community recognition and dispersal in vibrio cholerae biofilms. Nat. Commun. 16(1), 327 (2025) · DOI
- J. Liu, Z. Liu, K. Chen, W. Chen, X. Fang, M. Li, X. Zhou, N. Ding, H. Lei, C. Guo, Kindlin-2 promotes rear focal adhesion disassembly and directional persistence during cell migration. J. Cell Sci. 134(1), 244616 (2021) · DOI
- H. Zhang, K. Fichthorn, Structural classification of Ag and Cu nanocrystals with machine learning. Nanoscale 16(36), 17154–17164 (2024). https://doi.org/10.1039/D4NR02531H · DOI
- H. Fu, H. Bian, X. Shao, W. Cai, Collective variable-based enhanced sampling: from human learning to machine learning. J. Phys. Chem. Lett. 15(6), 1774–1783 (2024). https://doi.org/10.1021/acs.jpclett.3c03542 · DOI
- B. Yin, J. Wang, W. Du, P. Wang, P. Ying, H. Jia, Z. Zhang, Y. Du, C. Gomes, C. Duan, G. Henkelman, H. Xiao, AlphaNet: scaling up local-frame-based neural network interatomic potentials. NPJ Comput. Mater. 11(1), 332 (2025). https://doi.org/10.1038/s41524-025-01817-w · DOI
- J. Choi, G. Nam, J. Choi, Y. Jung, A perspective on foundation models in chemistry. JACS Au 5(4), 1499–1518 (2025). https://doi.org/10.1021/jacsau.4c01160 · DOI
- Y. Lee, X. Chen, S.M. Gericke, M. Li, D.N. Zakharov, A.R. Head, J.C. Yang, A.N. Alexandrova, Machine-learning-driven exploration of surface reconstructions of reduced rutile TiO2. Angew. Chem. 137(26), 202501017 (2025). https://doi.org/10.1002/ange.202501017 · DOI
- W. Li, D. Chen, Z. Lou, H. Yuan, X. Fu, H.Y. Lin, M. Lin, Y. Hou, H. Qi, P.F. Liu, H.G. Yang, H. Wang, Inhibiting overoxidation of dynamically evolved RuO2 to achieve a win-win in activity-stability for acidic water electrolysis. J. Am. Chem. Soc. 147(12), 10446–10458 (2025). https://doi.org/10.1021/jacs.4c18300 · DOI
- B. Deng, Y. Choi, P. Zhong, J. Riebesell, S. Anand, Z. Li, K. Jun, K.A. Persson, G. Ceder, Systematic softening in universal machine learning interatomic potentials. NPJ Comput. Mater. 11(1), 9 (2025). https://doi.org/10.1038/s41524-024-01500-6 · DOI
- D. Yoo, J. Jung, W. Jeong, S. Han, Metadynamics sampling in atomic environment space for collecting training data for machine learning potentials. NPJ Comput. Mater. 7(1), 131 (2021). https://doi.org/10.1038/s41524-021-00595-5 · DOI
- Z. Lian, F. Dattila, N. López, Stability and lifetime of diffusion-trapped oxygen in oxide-derived copper CO2 reduction electrocatalysts. Nat. Catal. 7(4), 401–411 (2024). https://doi.org/10.1038/s41929-024-01132-5 · DOI
- C. Yang, C. Wu, W. Xie, D. Xie, P. Hu, General reactive element-based machine learning potentials for heterogeneous catalysis. Nat. Catal. 8(9), 891–904 (2025). https://doi.org/10.1038/s41929-025-01398-3 · DOI
- M. MacIsaac, S. Bavdekar, D. Spearot, G. Subhash, A genetic algorithm trained machine-learned interatomic potential for the silicon-carbon system. J. Phys. Chem. C 128(29), 12213–12226 (2024). https://doi.org/10.1021/acs.jpcc.4c02205 · DOI
- N. Rønne, A. Aspuru-Guzik, B. Hammer, Generative diffusion model for surface structure discovery. Phys. Rev. B 110(23), 235427 (2024). https://doi.org/10.1103/PhysRevB.110.235427 · DOI
- C. Duan, G.-H. Liu, Y. Du, T. Chen, Q. Zhao, H. Jia, C.P. Gomes, E.A. Theodorou, H.J. Kulik, Optimal transport for generating transition states in chemical reactions. Nat. Mach. Intell. 7(4), 615–626 (2025). https://doi.org/10.1038/s42256-025-01010-0 · DOI
- B. Roldán Cuenya, M.A. Bañares, Introduction: operando and in situ studies in catalysis and electrocatalysis. Chem. Rev. 124(13), 8011–8013 (2024). https://doi.org/10.1021/acs.chemrev.4c00184 · DOI
- M. Monai, A new look at catalyst surfaces at work: introducing mixed isotope operando infrared spectroscopy (mioirs). ACS Catal. 15(2), 1363–1386 (2025) · DOI
- Z. Shi, Q. Li, H. Mishra, D. Ma, H.D. Abruña, D.A. Muller, Electron ptychography images hydrogen atom superlattices and 3D inhomogeneities in palladium hydride nanoparticles. J. Am. Chem. Soc. 147(43), 39020–39025 (2025). https://doi.org/10.1021/jacs.5c13741 · DOI
- B.M. Tackett, D. Raciti, A.R. Hight Walker, T.P. Moffat, Surface hydride formation on Cu(111) and its decomposition to form H2 in acid electrolytes. J. Phys. Chem. Lett. 12(44), 10936–10941 (2021). https://doi.org/10.1021/acs.jpclett.1c03131 · DOI
- R.G. Mariano, M. Kang, O.J. Wahab, I.J. McPherson, J.A. Rabinowitz, P.R. Unwin, M.W. Kanan, Microstructural origin of locally enhanced CO2 electroreduction activity on gold. Nat. Mater. 20(7), 1000–1006 (2021). https://doi.org/10.1038/s41563-021-00958-9 · DOI
- L. Zhang, M.E. Edwards, O.J. Wahab, H.Y. Samayoa-Oviedo, D.P. Freitas, X. Yan, L.A. Baker, Scanning electrochemical cell microscopy for sub-micrometer mass spectrometric studies of electrochemical reactions. ACS Electrochem. 1(7), 1066–1075 (2025). https://doi.org/10.1021/acselectrochem.5c00095 · DOI
- J. Lv, H. Zhang, D. Zhang, L. Liu, Y. Han, Low-dose electron microscopy imaging of electron beam-sensitive crystalline materials. Acc. Mater. Res. 3(5), 552–564 (2022). https://doi.org/10.1021/accountsmr.2c00008 · DOI
- M.C. Cendejas, O.A. Paredes Mellone, U. Kurumbail, Z. Zhang, J.H. Jansen, F. Ibrahim, S. Dong, J. Vinson, A.N. Alexandrova, D. Sokaras, S.R. Bare, I. Hermans, Tracking active phase behavior on Boron nitride during the oxidative dehydrogenation of propane using operando X-ray raman spectroscopy. J. Am. Chem. Soc. 145(47), 25686–25694 (2023). https://doi.org/10.1021/jacs.3c08679 · DOI
- R. Rana, J. Hong, A.S. Hoffman, B. Werghi, S.R. Bare, A.R. Kulkarni, Quantifying the site heterogeneities of non-uniform catalysts using QuantEXAFS. Chemistry–Methods 5(1), 202400020 (2025). https://doi.org/10.1002/cmtd.202400020 · DOI
Metadata
- Authors
- Zhang, Z., & Zhou, X.
- Affiliations
- SLAC National Accelerator Laboratory (US)
- The University of Texas at Austin (US)
- Corresponding author
- Zhang, Zisheng
- ORCID
- Zhang, Zisheng
- Venue
- MRS Communications
- Published
- 2025-12-22
- Volume
- 16
- Issue
- 1
- Pages
- 167-179
- ISSN
- 2159-6859 (ISSN-L)
- 2159-6867
- OpenAlex
- W7116664974
- Cited by
- 5
- References
- 3
- Citations by year
- 2026: 5
- FWCI
- 1.06
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- MRS Communications (publishedVersion)
- ChemRxiv (acceptedVersion, cc-by-nc-nd)
- Funders
- Stanford Precourt Institute for Energy
- Topics
- Physical Sciences › Materials Science › Materials Chemistry › Catalytic Processes in Materials Science
- Physical Sciences › Chemical Engineering › Catalysis › Catalysis and Oxidation Reactions
- Physical Sciences › Chemical Engineering › Catalysis › Catalysts for Methane Reforming
- Keywords
- catalyst surface structure, kinetic trapping, catalyst deactivation, catalyst design, machine learning for catalysis, reaction mechanism
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review