REFERENCES

1. IPCC. Climate Change 2023: Synthesis Report. A report of the intergovernmental panel on climate change. https://www.ipcc.ch/report/ar6/syr/downloads/report/IPCC_AR6_SYR_FullVolume.pdf. (accessed 2026-09-30).

2. Nagireddi, S.; Agarwal, J. R.; Vedapuri, D. Carbon dioxide capture, utilization, and sequestration: current status, challenges, and future prospects for global decarbonization. ACS. Eng. Au. 2024, 4, 22-48.

3. Nitopi, S.; Bertheussen, E.; Scott, S. B.; et al. Progress and perspectives of electrochemical CO2 reduction on copper in aqueous electrolyte. Chem. Rev. 2019, 119, 7610-72.

4. Bagger, A.; Ju, W.; Varela, A. S.; Strasser, P.; Rossmeisl, J. Electrochemical CO2 reduction: a classification problem. Chemphyschem 2017, 18, 3266-73.

5. Hori, Y.; Kikuchi, K.; Suzuki, S. Production of CO and CH4 in electrochemical reduction of CO2 at metal electrodes in aqueous hydrogencarbonate solution. Chem. Lett. 1985, 14, 1695-8.

6. Garza, A. J.; Bell, A. T.; Head-Gordon, M. Mechanism of CO2 reduction at copper surfaces: pathways to C2 products. ACS. Catal. 2018, 8, 1490-9.

7. Peterson, A. A.; Nørskov, J. K. Activity descriptors for CO2 electroreduction to methane on transition-metal catalysts. J. Phys. Chem. Lett. 2012, 3, 251-8.

8. Huo, C.; Cao, X.; Ye, Z.; Li, Y.; Lu, T. Hierarchical bimetallic electrocatalyst with amorphous SnO layer for highly efficient electroreduction of CO2. ChemCatChem 2021, 13, 4931-6.

9. Calle-Vallejo, F.; Koper, M. T. Theoretical considerations on the electroreduction of CO to C2 species on Cu(100) electrodes. Angew. Chem. Int. Ed. Engl. 2013, 52, 7282-5.

10. Liu, C.; Hedström, S.; Stenlid, J. H.; Pettersson, L. G. M. Amorphous, periodic model of a copper electrocatalyst with subsurface oxygen for enhanced CO coverage and dimerization. J. Phys. Chem. C. 2019, 123, 4961-8.

11. Dattila, F.; Seemakurthi, R. R.; Zhou, Y.; López, N. Modeling operando electrochemical CO2 reduction. Chem. Rev. 2022, 122, 11085-130.

12. Re Fiorentin, M.; Bianchi, M. G.; Christiansen, M. A. H.; et al. Methodological frameworks for computational electrocatalysis: from theory to practice. Small. Methods. 2026, 10, e01542.

13. Govindarajan, N.; Kastlunger, G.; Gauthier, J. A.; et al. The intricacies of computational electrochemistry. ACS. Energy. Lett. 2025, 10, 4277-88.

14. Li, Y.; Sun, Y.; Yu, M. Strategies for improving product selectivity in electrocatalytic carbon dioxide reduction using copper‐based catalysts. Adv. Funct. Mater. 2024, 34, 2410186.

15. Wang, Z.; Zhou, Y.; Qiu, P.; et al. Advanced catalyst design and reactor configuration upgrade in electrochemical carbon dioxide conversion. Adv. Mater. 2023, 35, e2303052.

16. Nørskov, J. K.; Rossmeisl, J.; Logadottir, A.; et al. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. J. Phys. Chem. B. 2004, 108, 17886-92.

17. Chan, K. A few basic concepts in electrochemical carbon dioxide reduction. Nat. Commun. 2020, 11, 5954.

18. Kastlunger, G.; Wang, L.; Govindarajan, N.; et al. Using pH dependence to understand mechanisms in electrochemical CO reduction. ACS. Catal. 2022, 12, 4344-57.

19. Qin, X.; Hansen, H. A.; Honkala, K.; Melander, M. M. Cation-induced changes in the inner- and outer-sphere mechanisms of electrocatalytic CO2 reduction. Nat. Commun. 2023, 14, 7607.

20. Melander, M. M.; Wu, T.; Weckman, T.; Honkala, K. Constant inner potential DFT for modelling electrochemical systems under constant potential and bias. npj. Comput. Mater. 2024, 10, 1184.

21. Brimley, P.; Almajed, H.; Alsunni, Y.; et al. Electrochemical CO2 reduction over metal-/nitrogen-doped graphene single-atom catalysts modeled using the grand-canonical density functional theory. ACS. Catal. 2022, 12, 10161-71.

22. Alsunni, Y. A.; Alherz, A. W.; Musgrave, C. B. Electrocatalytic reduction of CO2 to CO over Ag(110) and Cu(211) modeled by grand-canonical density functional theory. J. Phys. Chem. C. 2021, 125, 23773-83.

23. Hossain, M. D.; Huang, Y.; Yu, T. H.; Goddard, W. A. I. I. I.; Luo, Z. Reaction mechanism and kinetics for CO2 reduction on nickel single atom catalysts from quantum mechanics. Nat. Commun. 2020, 11, 2256.

24. Liu, H.; Yang, B. Potential-dependent C-C coupling mechanism and activity of C2 formation in the electrocatalytic reduction of CO2 on defective Cu(100) surfaces. Chem. Commun. 2022, 58, 709-12.

25. Wexler, R. B.; Qiu, T.; Rappe, A. M. Automatic prediction of surface phase diagrams using ab initio grand canonical Monte Carlo. J. Phys. Chem. C. 2019, 123, 2321-8.

26. Meng, J.; Freeze, J.; Nowack, L.; et al. Competitive carbonate binding hinders electrochemical CO2 reduction to CO on Cu surfaces at low overpotentials. J. Am. Chem. Soc. 2025, 147, 25361-71.

27. Verga, L. G.; Wang, Y.; Chakraborty, T.; Da Silva, J. L. F.; Mueller, T. The effects of near-surface atomic order on the catalytic properties of Cu3Au and CuAu3 intermetallics for the CO2 reduction reaction. Catal. Sci. Technol. 2023, 13, 6415-30.

28. Zhang, S.; Tang, Q.; Zhu, B.; Gao, Y. Reaction-driven varieties of active sites on Cu(100) in electrochemical CO2 reduction reaction. ACS. Catal. 2025, 15, 6497-506.

29. Zhang, S.; Lv, H. B.; Shi, Z. Z.; Wang, R.; Zheng, S.; Li, J. F. Subsurface hydrogen as a hidden driver of copper surface reconstruction in CO2 electroreduction. Natl. Sci. Rev. 2026, 13, nwag128.

30. Tang, Q.; Zhang, S.; Zhu, B.; Gao, Y. In situ reconstruction of a Cu(100) surface for promoted C–C coupling in CO2 electroreduction from first-principles multiscale modeling. ACS. Catal. 2026, 16, 1325-37.

31. Tian, X.; Tosello Gardini, A.; Raucci, U.; Xiao, H.; Zhuo, Y.; Parrinello, M. Electrochemical potential-driven water dynamics control CO2 electroreduction at the Ag/H2O interface. Nat. Commun. 2025, 16, 10636.

32. Sundararaman, R.; Vigil-Fowler, D.; Schwarz, K. Improving the accuracy of atomistic simulations of the electrochemical interface. Chem. Rev. 2022, 122, 10651-74.

33. Qin, X.; Vegge, T.; Hansen, H. A. Cation-coordinated inner-sphere CO2 electroreduction at Au-water interfaces. J. Am. Chem. Soc. 2023, 145, 1897-905.

34. Cheng, T.; Xiao, H.; Goddard, W. A. 3rd. Full atomistic reaction mechanism with kinetics for CO reduction on Cu(100) from ab initio molecular dynamics free-energy calculations at 298 K. Proc. Natl. Acad. Sci. U. S. A. 2017, 114, 1795-800.

35. Bussi, G.; Laio, A. Using metadynamics to explore complex free-energy landscapes. Nat. Rev. Phys. 2020, 2, 200-12.

36. Johnson, E.; Haussener, S. Contrasting views of the electric double layer in electrochemical CO2 reduction: continuum models vs molecular dynamics. J. Phys. Chem. C. Nanomater. Interfaces. 2024, 128, 10450-64.

37. Antolínez, S.; Jones, P. E.; Phillips, J. C.; Hadden-Perilla, J. A. AMBERff at scale: multimillion-atom simulations with AMBER force fields in NAMD. J. Chem. Inf. Model. 2024, 64, 543-54.

38. Chmiela, S.; Sauceda, H. E.; Müller, K. R.; Tkatchenko, A. Towards exact molecular dynamics simulations with machine-learned force fields. Nat. Commun. 2018, 9, 3887.

39. Groß, A.; Sakong, S. Ab initio simulations of water/metal interfaces. Chem. Rev. 2022, 122, 10746-76.

40. Cheng, T.; Xiao, H.; Goddard, W. A. 3rd. Reaction mechanisms for the electrochemical reduction of CO2 to CO and formate on the Cu(100) surface at 298 K from quantum mechanics free energy calculations with explicit water. J. Am. Chem. Soc. 2016, 138, 13802-5.

41. Senftle, T. P.; Hong, S.; Islam, M. M.; et al. The ReaxFF reactive force-field: development, applications and future directions. npj. Comput. Mater. 2016, 2, 15011.

42. Harrison, J. A.; Schall, J. D.; Maskey, S.; Mikulski, P. T.; Knippenberg, M. T.; Morrow, B. H. Review of force fields and intermolecular potentials used in atomistic computational materials research. Appl. Phys. Rev. 2018, 5, 031104.

43. van Duin, A. C. T.; Dasgupta, S.; Lorant, F.; Goddard, W. A. ReaxFF: a reactive force field for hydrocarbons. J. Phys. Chem. A. 2001, 105, 9396-409.

44. Buckley, A. K.; Lee, M.; Cheng, T.; et al. Electrocatalysis at organic-metal interfaces: identification of structure-reactivity relationships for CO2 reduction at modified Cu surfaces. J. Am. Chem. Soc. 2019, 141, 7355-64.

45. Unke, O. T.; Chmiela, S.; Sauceda, H. E.; et al. Machine learning force fields. Chem. Rev. 2021, 121, 10142-86.

46. Jinnouchi, R.; Minami, S. Machine learning force fields in electrochemistry: from fundamentals to applications. ACS. Nano. 2025, 19, 22600-44.

47. Jinnouchi, R.; Lahnsteiner, J.; Karsai, F.; Kresse, G.; Bokdam, M. Phase transitions of hybrid perovskites simulated by machine-learning force fields trained on the fly with bayesian inference. Phys. Rev. Lett. 2019, 122, 225701.

48. Jinnouchi, R.; Karsai, F.; Verdi, C.; Asahi, R.; Kresse, G. Descriptors representing two- and three-body atomic distributions and their effects on the accuracy of machine-learned inter-atomic potentials. J. Chem. Phys. 2020, 152, 234102.

49. Wang, R.; Fang, S.; Huang, Q.; Liu, Y. Constant-potential machine learning force field for the electrochemical interface. J. Chem. Theory. Comput. 2025, 21, 7628-35.

50. Zhang, L.; Han, J.; Wang, H.; Saidi, W. A.; Car, R.; E, W. End-to-end symmetry preserving inter-atomic potential energy model for finite and extended systems. arXiv 2018, arXiv:1805.09003. Available online: https://doi.org/10.48550/arXiv.1805.09003. (accessed 2026-09-30).

51. Batatia, I.; Kovács, D. P.; Simm, G. N. C.; Ortner, C.; Csányi, G. MACE: higher order equivariant message passing neural networks for fast and accurate force fields. arXiv 2022, arXiv:2206.07697. Available online: https://doi.org/10.48550/arXiv.2206.07697. (accessed 2026-09-30).

52. Schran, C.; Behler, J.; Marx, D. Automated fitting of neural network potentials at coupled cluster accuracy: protonated water clusters as testing ground. J. Chem. Theory. Comput. 2020, 16, 88-99.

53. Xing, M.; Zhang, Y.; Li, S.; He, H.; Sun, S. Prediction of carbon dioxide reduction catalyst using machine learning with a few-feature model: WLEDZ. J. Phys. Chem. C. 2022, 126, 17025-35.

54. Abraham, B. M.; Piqué, O.; Khan, M. A.; Viñes, F.; Illas, F.; Singh, J. K. Machine learning-driven discovery of key descriptors for CO2 activation over two-dimensional transition metal carbides and nitrides. ACS. Appl. Mater. Interfaces. 2023, 15, 30117-26.

55. Chen, H.; Yin, J.; Li, J.; Wang, X. Theoretical high-throughput screening of single-atom CO2 electroreduction catalysts to methanol using active learning. Engineering 2025, 52, 172-82.

56. Anselmi, M.; Slabaugh, G.; Crespo-Otero, R.; Di Tommaso, D. Molecular graph transformer: stepping beyond ALIGNN into long-range interactions. Digit. Discov. 2024, 3, 1048-57.

57. Wan, X.; Zhang, Z.; Niu, H.; et al. Machine-learning-accelerated catalytic activity predictions of transition metal phthalocyanine dual-metal-site catalysts for CO2 reduction. J. Phys. Chem. Lett. 2021, 12, 6111-8.

58. Mok, D. H.; Li, H.; Zhang, G.; Lee, C.; Jiang, K.; Back, S. Data-driven discovery of electrocatalysts for CO2 reduction using active motifs-based machine learning. Nat. Commun. 2023, 14, 7303.

59. Wang, Z.; Sun, Z.; Yin, H.; et al. The role of machine learning in carbon neutrality: catalyst property prediction, design, and synthesis for carbon dioxide reduction. eScience 2023, 3, 100136.

60. Noh, J.; Chang, H. Data-driven prediction of configurational stability of molecule-adsorbed heterogeneous catalysts. J. Chem. Inf. Model. 2023, 63, 5981-95.

61. Tran, R.; Lan, J.; Shuaibi, M.; et al. The open catalyst 2022 (OC22) dataset and challenges for oxide electrocatalysts. ACS. Catal. 2023, 13, 3066-84.

62. Gholizadeh, R.; Pavlin, M.; Huš, M.; Likozar, B. Multiscale modeling of CO2 electrochemical reduction on copper electrocatalysts: a review of advancements, challenges, and future directions. ChemSusChem 2025, 18, e202400898.

63. Raciti, D.; Mao, M.; Wang, C. Mass transport modelling for the electroreduction of CO2 on Cu nanowires. Nanotechnology 2018, 29, 044001.

64. Gupta, N.; Gattrell, M.; Macdougall, B. Calculation for the cathode surface concentrations in the electrochemical reduction of CO2 in KHCO3 solutions. J. Appl. Electrochem. 2006, 36, 161-72.

65. Vinogradova, O.; Krishnamurthy, D.; Pande, V.; Viswanathan, V. Quantifying confidence in DFT-predicted surface pourbaix diagrams of transition-metal electrode-electrolyte interfaces. Langmuir 2018, 34, 12259-69.

66. Anderson, A. B. Pourbaix diagrams for H2O oxidation to adsorbed OH on Pt(111) and why they differ from those for bulk solids. J. Phys. Chem. C. 2018, 122, 9958-64.

67. Russell, A. E. Electrocatalysis: theory and experiment at the interface. Phys. Chem. Chem. Phys. 2008, 10, 3607-8.

68. Weitzner, S. E.; Dabo, I. Quantum–continuum simulation of underpotential deposition at electrified metal–solution interfaces. npj. Comput. Mater. 2017, 3, 4.

69. Hori, Y.; Murata, A.; Takahashi, R. Formation of hydrocarbons in the electrochemical reduction of carbon dioxide at a copper electrode in aqueous solution. J. Chem. Soc. Faraday. Trans. 1. 1989, 85, 2309.

70. Ooka, H.; Huang, J.; Exner, K. S. The sabatier principle in electrocatalysis: basics, limitations, and extensions. Front. Energy. Res. 2021, 9, 654460.

71. Cai, J.; Zhao, Q.; Hsu, W. Y.; et al. Highly selective electrochemical reduction of CO2 into methane on nanotwinned Cu. J. Am. Chem. Soc. 2023, 145, 9136-43.

72. Huang, Y.; Handoko, A. D.; Hirunsit, P.; Yeo, B. S. Electrochemical reduction of CO2 using copper single-crystal surfaces: effects of CO* coverage on the selective formation of ethylene. ACS. Catal. 2017, 7, 1749-56.

73. Cheng, D.; Nguyen, K. C.; Sumaria, V.; et al. Structure sensitivity and catalyst restructuring for CO2 electro-reduction on copper. Nat. Commun. 2025, 16, 4064.

74. Zhu, C.; Zhang, Z.; Zhong, L.; et al. Product-specific active site motifs of Cu for electrochemical CO2 reduction. Chem 2021, 7, 406-20.

75. Verga, L. G.; Mendes, P. C. D.; Ocampo-Restrepo, V. K.; Da Silva, J. L. F. The role of site coordination on the CO2 electroreduction pathway on stepped and defective copper surfaces. Catal. Sci. Technol. 2021, 11, 2770-81.

76. Gholizadeh, R.; Pavlin, M.; Likozar, B.; Huš, M. Why including solvation is paramount: first-principles calculations of electrochemical CO2 reduction to CO on a Cu electrocatalyst. Chempluschem 2025, 90, e202400346.

77. Kowalec, I.; Kabalan, L.; Catlow, C. R. A.; Logsdail, A. J. A computational study of direct CO2 hydrogenation to methanol on Pd surfaces. Phys. Chem. Chem. Phys. 2022, 24, 9360-73.

78. Chang, C. C.; Ku, M. S. Role of high-index facet Cu(711) surface in controlling the C2 selectivity for CO2 reduction reaction - a DFT study. J. Phys. Chem. C. 2021, 125, 10919-25.

79. Song, M.; Jiao, Z.; Jing, W.; Liu, Y.; Guo, L. Revealing the nature of C-C coupling sites on a Cu surface for CO2 reduction. J. Phys. Chem. Lett. 2022, 13, 4434-40.

80. Lin, W.; Ghulam Nabi, A.; Palma, M.; Di Tommaso, D. Copper nanowires for electrochemical CO2 reduction reaction. ACS. Appl. Nano. Mater. 2024, 7, 27883-98.

81. Xu, Y.; Li, F.; Xu, A.; et al. Low coordination number copper catalysts for electrochemical CO2 methanation in a membrane electrode assembly. Nat. Commun. 2021, 12, 2932.

82. Raju, R. K.; Rodriguez, P.; Johnston, R. L. Can a single valence electron alter the electrocatalytic activity and selectivity for CO2 reduction on the subnanometer scale? J. Phys. Chem. C. 2019, 123, 14591-609.

83. Wu, Q. J.; Si, D. H.; Sun, P. P.; et al. Atomically precise copper nanoclusters for highly efficient electroreduction of CO2 towards hydrocarbons via breaking the coordination symmetry of Cu site. Angew. Chem. Int. Ed. Engl. 2023, 62, e202306822.

84. Reske, R.; Mistry, H.; Behafarid, F.; Roldan Cuenya, B.; Strasser, P. Particle size effects in the catalytic electroreduction of CO2 on Cu nanoparticles. J. Am. Chem. Soc. 2014, 136, 6978-86.

85. Mistry, H.; Behafarid, F.; Reske, R.; Varela, A. S.; Strasser, P.; Roldan Cuenya, B. Tuning catalytic selectivity at the mesoscale via interparticle interactions. ACS. Catal. 2016, 6, 1075-80.

86. Bu, Y.; Zhao, M.; Zhang, G.; Zhang, X.; Gao, W.; Jiang, Q. Electroreduction of CO2 on Cu clusters: the effects of size, symmetry, and temperature. ChemElectroChem 2019, 6, 1831-7.

87. Nabi, A. G.; Ur-Rehman, A.; Hussain, A.; Di Tommaso, D. Ab initio random structure searching and catalytic properties of copper-based nanocluster with Earth-abundant metals for the electrocatalytic CO2-to-CO conversion. Mol. Catal. 2022, 527, 112406.

88. Duan, Y. X.; Meng, F. L.; Liu, K. H.; et al. Amorphizing of Cu nanoparticles toward highly efficient and robust electrocatalyst for CO2 reduction to liquid fuels with high Faradaic efficiencies. Adv. Mater. 2018, 30, e1706194.

89. Xiong, Y.; Wei, B.; Wu, M.; et al. Rapid synthesis of amorphous bimetallic copper-bismuth electrocatalysts for efficient electrochemical CO2 reduction to formate in a wide potential window. J. CO2. Util. 2021, 51, 101621.

90. Chen, C.; Yan, X.; Wu, Y.; et al. Oxidation of metallic Cu by supercritical CO2 and control synthesis of amorphous nano-metal catalysts for CO2 electroreduction. Nat. Commun. 2023, 14, 1092.

91. Song, M.; Jiao, Z.; Jing, W.; Liu, Y.; Guo, L. How *CO spill-over affects C–C coupling on amorphous Cu for converting CO2 to multi-carbon products. J. Catal. 2023, 428, 115170.

92. Muthuperiyanayagam, A.; Di Tommaso, D. Impact of amorphous structure on CO2 electrocatalysis with Cu: a combined machine learning forcefield and DFT modelling approach. Electrochim. Acta. 2024, 507, 145188.

93. Muthuperiyanayagam, A.; Pedretti, E.; Righi, M. C.; Tommaso, D. D. Optimized selectivity in CO2 electrochemical reduction using amorphous CuNi catalysts: insights from density functional theory and machine learning simulations. J. Energy. Chem. 2026, 112, 1014-25.

94. Feng, Y.; An, W.; Wang, Z.; Wang, Y.; Men, Y.; Du, Y. Electrochemical CO2 reduction reaction on M@Cu(211) bimetallic single-atom surface alloys: mechanism, kinetics, and catalyst screening. ACS. Sustain. Chem. Eng. 2020, 8, 210-22.

95. Liu, T.; Song, G.; Liu, X.; et al. Insights into the mechanism in electrochemical CO2 reduction over single-atom copper alloy catalysts: a DFT study. iScience 2023, 26, 107953.

96. Clark, E. L.; Hahn, C.; Jaramillo, T. F.; Bell, A. T. Electrochemical CO2 reduction over compressively strained CuAg surface alloys with enhanced multi-carbon oxygenate selectivity. J. Am. Chem. Soc. 2017, 139, 15848-57.

97. Zhi, X.; Jiao, Y.; Zheng, Y.; Vasileff, A.; Qiao, S. Selectivity roadmap for electrochemical CO2 reduction on copper-based alloy catalysts. Nano. Energy. 2020, 71, 104601.

98. Li, Z.; Wang, P.; Lyu, X.; et al. Directing CO2 electroreduction pathways for selective C2 product formation using single-site doped copper catalysts. Nat. Chem. Eng. 2024, 1, 159-69.

99. Wang, T.; Dong, C.; Lin, J.; et al. Recent advances in carbon dioxide conversion: a circular bioeconomy perspective. Sustainability 2021, 13, 6962.

100. Barberini, F.; Barile, A.; Restuccia, P.; et al. Dopant redox stability as a design principle for selective CO2 electroreduction on Cu. Phys. Chem. Chem. Phys. 2026, 28, 21230-45.

101. Hoffman, Z. B.; Gray, T. S.; Moraveck, K. B.; Gunnoe, T. B.; Zangari, G. Electrochemical reduction of carbon dioxide to syngas and formate at dendritic copper–indium electrocatalysts. ACS. Catal. 2017, 7, 5381-90.

102. Zhang, M.; Zhang, Z.; Zhao, Z.; et al. Tunable selectivity for electrochemical CO2 reduction by bimetallic Cu–Sn catalysts: elucidating the roles of Cu and Sn. ACS. Catal. 2021, 11, 11103-8.

103. Wan, L.; Zhang, X.; Cheng, J.; et al. Bimetallic Cu–Zn catalysts for electrochemical CO2 reduction: phase-separated versus core–shell distribution. ACS. Catal. 2022, 12, 2741-8.

104. Mitchell, S.; Pérez-Ramírez, J. Single atom catalysis: a decade of stunning progress and the promise for a bright future. Nat. Commun. 2020, 11, 4302.

105. Nguyen, T. N.; Salehi, M.; Le, Q. V.; Seifitokaldani, A.; Dinh, C. T. Fundamentals of electrochemical CO2 reduction on single-metal-atom catalysts. ACS. Catal. 2020, 10, 10068-95.

106. Zhang, J.; Cai, W.; Hu, F. X.; Yang, H.; Liu, B. Recent advances in single atom catalysts for the electrochemical carbon dioxide reduction reaction. Chem. Sci. 2021, 12, 6800-19.

107. Liang, Y.; Wu, C.; Meng, S.; et al. Ag single atoms anchored on CeO2 with interfacial oxygen vacancies for efficient CO2 electroreduction. ACS. Appl. Mater. Interfaces. 2023, 15, 30262-71.

108. Yang, Z.; Zhang, J.; Tan, X.; et al. Manipulating the coordination environment of Cu single atoms via regulating ZrO2 support crystal phases for enhanced CO2 electroreduction. J. Am. Chem. Soc. 2025, 147, 35985-94.

109. Chen, R.; Zhao, J.; Zhang, X.; et al. Visualizing catalytic dynamics of single-Cu-atom-modified SnS2 in CO2 electroreduction via rapid freeze-quench Mössbauer spectroscopy. J. Am. Chem. Soc. 2024, 146, 24368-76.

110. Lin, Y.; Wang, M.; Xiang, Y.; et al. MoS2 grain boundary-supported single-atom catalysts for efficient electrocatalytic CO2 conversion to CO. J. Phys. Chem. Lett. 2026, 17, 1805-14.

111. Yang, H.; Lin, Q.; Zhang, C.; et al. Carbon dioxide electroreduction on single-atom nickel decorated carbon membranes with industry compatible current densities. Nat. Commun. 2020, 11, 593.

112. Feng, J.; Gao, H.; Zheng, L.; et al. A Mn-N3 single-atom catalyst embedded in graphitic carbon nitride for efficient CO2 electroreduction. Nat. Commun. 2020, 11, 4341.

113. Qiao, B.; Wang, A.; Yang, X.; et al. Single-atom catalysis of CO oxidation using Pt1/FeOx. Nat. Chem. 2011, 3, 634-41.

114. Martini, A.; Hursán, D.; Timoshenko, J.; et al. Tracking the evolution of single-atom catalysts for the CO2 electrocatalytic reduction using operando X-ray absorption spectroscopy and machine learning. J. Am. Chem. Soc. 2023, 145, 17351-66.

115. Kim, H.; Shin, D.; Yang, W.; et al. Identification of single-atom Ni site active toward electrochemical CO2 conversion to CO. J. Am. Chem. Soc. 2021, 143, 925-33.

116. Pei, J.; Shang, H.; Mao, J.; et al. A replacement strategy for regulating local environment of single-atom Co-SxN4-x catalysts to facilitate CO2 electroreduction. Nat. Commun. 2024, 15, 416.

117. Pan, F.; Li, B.; Sarnello, E.; et al. Pore-edge tailoring of single-atom iron–nitrogen sites on graphene for enhanced CO2 reduction. ACS. Catal. 2020, 10, 10803-11.

118. Zhang, H.; Wang, H.; Jia, S.; et al. CoN4 active sites in a graphene matrix for the highly efficient electrocatalysis of CO2 reduction. New. Carbon. Mater. 2022, 37, 734-42.

119. Bi, W.; Li, X.; You, R.; et al. Surface immobilization of transition metal ions on nitrogen-doped graphene realizing high-efficient and selective CO2 reduction. Adv. Mater. 2018, 30, e1706617.

120. Han, L.; Song, S.; Liu, M.; et al. Stable and efficient single-atom Zn catalyst for CO2 reduction to CH4. J. Am. Chem. Soc. 2020, 142, 12563-7.

121. Shang, H.; Wang, T.; Pei, J.; et al. Design of a single-atom indiumδ+-N4 interface for efficient electroreduction of CO2 to formate. Angew. Chem. Int. Ed. Engl. 2020, 59, 22465-9.

122. Bihua, H.; Hailin, C.; Zhiwei, L.; et al. Electronic regulation & improved conductivity of molecular catalysts as electrocatalysts. Catal. Sci. Technol. 2024, 14, 4127-31.

123. Shi, G.; Zhang, W.; Kang, Y.; et al. Nanoconfinement promotes CO2 electroreduction to methanol on a molecular catalyst. Nat. Commun. 2025, 16, 7359.

124. Tian, P.; Zhang, B.; Chen, J.; et al. Curvature-induced electronic tuning of molecular catalysts for CO2 reduction. Catal. Sci. Technol. 2021, 11, 2491-6.

125. Sui, R.; Wang, B.; Wang, Y.; et al. A general and facile calcination method to synthesize single-site catalysts for highly efficient electrochemical CO2 reduction. Nano. Res. 2024, 17, 3895-901.

126. Dai, Y.; Li, H.; Wang, C.; et al. Manipulating local coordination of copper single atom catalyst enables efficient CO2-to-CH4 conversion. Nat. Commun. 2023, 14, 3382.

127. Huang, M.; Deng, B.; Zhao, X.; et al. Template-sacrificing synthesis of well-defined asymmetrically coordinated single-atom catalysts for highly efficient CO2 electrocatalytic reduction. ACS. Nano. 2022, 16, 2110-9.

128. Su, P.; Iwase, K.; Nakanishi, S.; Hashimoto, K.; Kamiya, K. Nickel-nitrogen-modified graphene: an efficient electrocatalyst for the reduction of carbon dioxide to carbon monoxide. Small 2016, 12, 6083-9.

129. Gul, S.; Nasim, F.; Nadeem, M. A. Single-atom metal-based electrocatalysts (Fe, Ni, and Co) for CO2-to-CO conversion: a comprehensive review. ACS. Appl. Energy. Mater. 2025, 8, 11786-812.

130. Li, X.; Bi, W.; Chen, M.; et al. Exclusive Ni-N4 sites realize near-unity CO selectivity for electrochemical CO2 reduction. J. Am. Chem. Soc. 2017, 139, 14889-92.

131. Uddin, A. T.; Zhao, Q.; Toroz, D.; Crespo-Otero, R.; Di Tommaso, D. Computational screening of metalloporphyrin catalysts for the activation of carbon dioxide. Mol. Catal. 2024, 565, 114386.

132. Sarma, S. C.; Barrio, J.; Bagger, A.; et al. Reaching the fundamental limitation in CO2 reduction to CO with single atom catalysts. Adv. Funct. Mater. 2023, 33, 2302468.

133. Hung, S. F.; Xu, A.; Wang, X.; et al. A metal-supported single-atom catalytic site enables carbon dioxide hydrogenation. Nat. Commun. 2022, 13, 819.

134. Fauzi, A.; Chen, X.; Zhao, H.; et al. Recent progress of M-N-C single atom electrocatalysts for carbon dioxide reduction reaction. Next. Energy. 2023, 1, 100045.

135. Bai, X.; Zhao, Z.; Lu, G. Breaking the scaling relationship on single-atom embedded MBene for selective CO2 electroreduction. J. Phys. Chem. Lett. 2023, 14, 5172-80.

136. P, S.; John, J.; Rajan, T. P. D.; et al. Graphitic carbon nitride (g-C3N4) based heterogeneous single atom catalysts: synthesis, characterisation and catalytic applications. J. Mater. Chem. A. 2023, 11, 8599-646.

137. Zhu, H.; Liu, S.; Yu, J.; Chen, Q.; Mao, X.; Wu, T. Computational screening of effective g-C3N4 based single atom electrocatalysts for the selective conversion of CO2. Nanoscale 2023, 15, 8416-23.

138. Shui, H.; Li, G.; Fu, C.; et al. A DFT study on the structural properties and CO2 electrocatalytic reduction activity of monolayer graphitic carbon nitride supported Ag/Au single atom catalysts. Surf. Sci. 2025, 754, 122692.

139. Baskaran, S.; Jung, J. Mo2CS2-MXene supported single-atom catalysts for efficient and selective CO2 electrochemical reduction. Appl. Surf. Sci. 2022, 592, 153339.

140. Al-Mahayni, H.; Yuan, R.; Seifitokaldani, A. A MXene-supported single atom catalyst selectively converts CO2 into methanol and methane. RSC. Sustain. 2025, 3, 1729-40.

141. Ren, Y.; Sun, X.; Qi, K.; Zhao, Z. Single atom supported on MoS2 as efficient electrocatalysts for the CO2 reduction reaction: a DFT study. Appl. Surf. Sci. 2022, 602, 154211.

142. Ren, H.; Lang, Z.; Tan, H.; Wang, Y.; Li, Y. p-Block single-atom anchored MoS2 monolayer for efficient electroreduction of CO2 to formate via strong p–sp interaction. J. Phys. Chem. C. 2024, 128, 6702-10.

143. Sun, Y.; Liu, L.; Liu, J. Theoretical study on the electrochemical CO2 reduction performance of MoS2-supported Ni single atoms with transition metal substrate doping. Surf. Interfaces. 2024, 52, 104938.

144. Linghu, Y.; Tong, T.; Li, C.; Wu, C. The catalytic mechanism of CO2 electrochemical reduction over transition metal-modified 1T'-MoS2 monolayers. Appl. Surf. Sci. 2022, 590, 153001.

145. Wang, X.; Wang, C.; Ren, H.; et al. Accelerating proton and electron transfer enables highly active Fe–N–C catalyst for electrochemical CO2 reduction. Adv. Funct. Mater. 2024, 34, 2311818.

146. Ao, C.; Zhao, W.; Ruan, S.; et al. Theoretical investigations of electrochemical CO2 reduction by transition metals anchored on CNTs. Sustain. Energy. Fuels. 2020, 4, 6156-64.

147. Lin, W.; Di Tommaso, D. Screening nitrogen-coordinated single atom catalysts on armchair carbon nanotubes for enhanced electrochemical CO2 reduction to C1 products. ACS. Catal. 2025, 15, 16463-75.

148. Chen, Q.; Yang, H.; Wang, P.; Ke, Q.; Ge, X.; Chen, X. Charge transfer regulates electrocatalytic CO2 reduction on one-dimensional carbon nanotube/boron nitride nanotube heterostructures. Sep. Purif. Technol. 2025, 354, 128981.

149. Zhou, Y.; Chen, H. Electrocatalytic CO2 conversion on boron nitride nanotubes by metal single-atom engineering. Chem. Phys. Lett. 2024, 852, 141518.

150. Chen, Q.; Ke, Q.; Zhao, X.; Chen, X. Ruthenium-doped boron nitride nanotubes as promising electrocatalysts for carbon dioxide reduction to methane. Diamond. Relat. Mater. 2023, 136, 109942.

151. Ma, A.; Pang, Y.; Ding, Z.; Fan, G.; Xu, H. Curvature effect of TMN4 sites on carbon nanotube for electrochemical reduction of carbon dioxide revealed by machine learning. Electrochim. Acta. 2025, 537, 146862.

152. Lv, K.; Wan, D.; Pan, R.; Suo, W.; Zhu, Y. Curvature of NCNTs induced selectivity of CO2 electroreduction into CO. Carbon. Neutral. 2022, 1, 189-97.

153. Su, J.; Musgrave, C. B.; Song, Y.; et al. Strain enhances the activity of molecular electrocatalysts via carbon nanotube supports. Nat. Catal. 2023, 6, 818-28.

154. Jiang, K.; Siahrostami, S.; Zheng, T.; et al. Isolated Ni single atoms in graphene nanosheets for high-performance CO2 reduction. Energy. Environ. Sci. 2018, 11, 893-903.

155. Cui, Y.; Wu, Y.; Ren, C.; Li, Q.; Ling, C.; Wang, J. Beyond local coordination: how global structure engineers the selectivity of single atom catalysts for CO2 reduction. Angew. Chem. Int. Ed. Engl. 2026, 65, e19826.

156. Zhang, F.; Li, J.; Chen, Y.; et al. Highly coordinated Ni-N5 sites for efficient electrocatalytic CO2 reduction toward CO with Faradaic efficiency exceeding 99%. J. Catal. 2024, 433, 115495.

157. Kim, J. H.; Kim, J.; Ma, J.; et al. Spontaneous metal-chelation strategy for highly dense Ni single-atom catalysts with asymmetric coordination in CO2 electroreduction. Small 2025, 21, e2409481.

158. Liu, X.; Liao, L.; Xia, G.; et al. An accurate “metal pre-buried” strategy for constructing Ni–N2C2 single-atom sites with high metal loadings toward electrocatalytic CO2 reduction. J. Mater. Chem. A. 2022, 10, 25047-54.

159. Han, Y.; Wei, Y.; Goswami, A.; Alexandrova, A. Uncovering the true active sites in Ni-N-C catalysts for CO2 electroreduction. J. Am. Chem. Soc. 2025, 147, 38636-46.

160. Luo, Z.; Yin, Z.; Yu, J.; et al. General synthetic strategy to ordered mesoporous carbon catalysts with single-atom metal sites for electrochemical CO2 reduction. Small 2022, 18, e2107799.

161. Bao, Y.; Xiao, J.; Huang, Y.; et al. Regulating spin polarization via axial nitrogen traction at Fe-N5 sites enhanced electrocatalytic CO2 reduction for Zn-CO2 batteries. Angew. Chem. Int. Ed. Engl. 2024, 63, e202406030.

162. Kong, Y.; Jia, X.; Chai, X.; et al. Modulating the local microenvironment over isolated nickel sites through first-shell coordination to regulate the reaction pathway of CO2 electroreduction. Natl. Sci. Rev. 2025, 12, nwaf173.

163. Cao, S.; Wei, S.; Wei, X.; et al. Can N, S cocoordination promote single atom catalyst performance in CO2RR? Fe-N2S2 porphyrin versus Fe-N4 porphyrin. Small 2021, 17, e2100949.

164. Li, Y.; Li, Y.; Sun, H.; et al. Current status and perspectives of dual-atom catalysts towards sustainable energy utilization. Nanomicro. Lett. 2024, 16, 139.

165. Zhao, X.; Zhao, K.; Liu, Y.; et al. Highly efficient electrochemical CO2 reduction on a precise homonuclear diatomic Fe–Fe catalyst. ACS. Catal. 2022, 12, 11412-20.

166. Zhang, N.; Zhang, X.; Kang, Y.; et al. A supported Pd2 dual-atom site catalyst for efficient electrochemical CO2 reduction. Angew. Chem. Int. Ed. Engl. 2021, 60, 13388-93.

167. Liu, H.; Huang, Q.; An, W.; Wang, Y.; Men, Y.; Liu, S. Dual-atom active sites embedded in two-dimensional C2N for efficient CO2 electroreduction: a computational study. J. Energy. Chem. 2021, 61, 507-16.

168. Ma, Z.; Zhong, Z.; Dou, Y.; Zhang, X. Enhanced C–C coupling in CO2 electroreduction on dual-atom catalysts modified by bridge O/OH. Appl. Surf. Sci. 2024, 672, 160837.

169. Wang, Z.; Ma, A.; Liu, Z.; et al. Density functional theory study of transition metal dual-atom anchored phthalocyanine as high-performance electrocatalysts for carbon dioxide reduction reaction. Appl. Surf. Sci. 2024, 669, 160532.

170. Ren, W.; Tan, X.; Yang, W.; et al. Isolated diatomic Ni-Fe metal-nitrogen sites for synergistic electroreduction of CO2. Angew. Chem. Int. Ed. Engl. 2019, 58, 6972-6.

171. Zhao, Q.; Crespo-Otero, R.; Di Tommaso, D. The role of copper in enhancing the performance of heteronuclear diatomic catalysts for the electrochemical CO2 conversion to C1 chemicals. J. Energy. Chem. 2023, 85, 490-500.

172. Zhao, Z. H.; Huang, J. R.; Liao, P. Q.; Chen, X. M. Highly efficient electroreduction of CO2 to ethanol via asymmetric C-C coupling by a metal-organic framework with heterodimetal dual sites. J. Am. Chem. Soc. 2023, 145, 26783-90.

173. Chen, C.; Sun, Z.; Qin, G.; et al. Asymmetrically coordinated Cu dual-atom-sites enables selective CO2 electroreduction to ethanol. Adv. Mater. 2024, 36, e2409797.

174. Roongcharoen, T.; Mano, P.; Jitwatanasirikul, T.; et al. Theoretical insight on why N-vacancy promotes the selective CO2 reduction to ethanol on NiMn doped graphitic carbon nitride sheets. Appl. Surf. Sci. 2022, 595, 153527.

175. Bai, Z.; Zhi, Z.; Jiang, X. Z.; Luo, K. H. Rational design of dual-atom catalysts for electrochemical CO2 reduction to C1 and C2 products with high activity and selectivity: a density functional theory study. Ind. Eng. Chem. Res. 2025, 64, 4378-87.

176. Sun, G.; Cao, Y.; Li, D.; et al. Dual-atom Cu2/N-doped carbon catalyst for electroreduction of CO2 to C2H4. Appl. Catal. A. Gen. 2023, 651, 119025.

177. Hensley, A. J. R.; Ghale, K.; Rieg, C.; et al. DFT-based method for more accurate adsorption energies: an adaptive sum of energies from RPBE and vdW density functionals. J. Phys. Chem. C. 2017, 121, 4937-45.

178. Lei, J.; Zhu, T. Impact of potential and active-site environment on single-iron-atom-catalyzed electrochemical CO2 reduction from accurate quantum many-body simulations. ACS. Catal. 2024, 14, 3933-42.

179. Zhi, X.; Jiao, Y.; Zheng, Y.; Qiao, S. Z. Impact of interfacial electron transfer on electrochemical CO2 reduction on graphitic carbon nitride/doped graphene. Small 2019, 15, e1804224.

180. Wang, Y.; Tian, Y.; Yan, L.; Su, Z. DFT study on sulfur-doped g-C3N4 nanosheets as a photocatalyst for CO2 reduction reaction. J. Phys. Chem. C. 2018, 122, 7712-9.

181. Siahrostami, S.; Jiang, K.; Karamad, M.; Chan, K.; Wang, H.; Nørskov, J. Theoretical investigations into defected graphene for electrochemical reduction of CO2. ACS. Sustain. Chem. Eng. 2017, 5, 11080-5.

182. Mishra, A. K.; Roldan, A.; de Leeuw, N. H. A density functional theory study of the adsorption behaviour of CO2 on Cu2O surfaces. J. Chem. Phys. 2016, 145, 044709.

183. Gallagher, C.; Zhao, Q. Multireference wavefunction methods for accurate adsorption energies on single-atom catalysts. J. Catal. 2026, 462, 117069.

184. Misra, D.; Di Liberto, G.; Pacchioni, G. CO2 electroreduction on single atom catalysts: the role of the DFT functional. Phys. Chem. Chem. Phys. 2024, 26, 10746-56.

185. He, S.; Cao, G.; Nie, J.; Li, S.; Ren, J. Essential role of self-interaction correction in single-atom catalysis: from electronic structure to activity predictions. Phys. Rev. B. 2026, 113, 235413.

186. Han, Z.; Han, D.; Chen, Z.; et al. Steering surface reconstruction of copper with electrolyte additives for CO2 electroreduction. Nat. Commun. 2022, 13, 3158.

187. Zhu, J.; Chen, J. L.; Qi, X. Z.; et al. Electron-rich subnanometer Cu clusters facilitate CO-CO coupling in CO2 electroreduction. J. Am. Chem. Soc. 2026, 148, 4008-19.

188. Duan, Z.; Henkelman, G. Surface charge and electrostatic spin crossover effects in CoN4 electrocatalysts. ACS. Catal. 2020, 10, 12148-55.

189. Shen, J.; Kolb, M. J.; Göttle, A. J.; Koper, M. T. M. DFT study on the mechanism of the electrochemical reduction of CO2 catalyzed by cobalt porphyrins. J. Phys. Chem. C. 2016, 120, 15714-21.

190. Sun, M.; Staykov, A.; Yamauchi, M. Understanding the roles of hydroxide in CO2 electroreduction on a Cu electrode for achieving variable selectivity. ACS. Catal. 2022, 12, 14856-63.

191. Li, C.; Guo, Z.; Liu, Z.; et al. Boosting electrochemical CO2 reduction via surface hydroxylation over Cu-based electrocatalysts. ACS. Catal. 2023, 13, 16114-25.

192. Iijima, G.; Inomata, T.; Yamaguchi, H.; Ito, M.; Masuda, H. Role of a hydroxide layer on Cu electrodes in electrochemical CO2 reduction. ACS. Catal. 2019, 9, 6305-19.

193. Cao, Y.; Chen, Z.; Li, P.; et al. Surface hydroxide promotes CO2 electrolysis to ethylene in acidic conditions. Nat. Commun. 2023, 14, 2387.

194. Buckley, A. K.; Cheng, T.; Oh, M. H.; et al. Approaching 100% selectivity at low potential on Ag for electrochemical CO2 reduction to CO using a surface additive. ACS. Catal. 2021, 11, 9034-42.

195. Xu, W.; Qiu, Y.; Zhang, T.; Li, X.; Zhang, H. The effect of organic additives on the activity and selectivity of CO2 electroreduction: the role of functional groups. ChemSusChem 2018, 11, 2904-11.

196. Qiu, Y.; Zhong, H.; Xu, W.; Zhang, T.; Li, X.; Zhang, H. Tuning the electrocatalytic properties of a Cu electrode with organic additives containing amine group for CO2 reduction. J. Mater. Chem. A. 2019, 7, 5453-62.

197. Wang, H.; Lu, R.; Dong, C.; Du, X.; Liang, H. Glycine modified copper promotes CO2 electroreduction to multi-carbon products: a computational study. Phys. Chem. Chem. Phys. 2024, 26, 22314-8.

198. Wang, J.; Cheng, T.; Fenwick, A. Q.; et al. Selective CO2 electrochemical reduction enabled by a tricomponent copolymer modifier on a copper surface. J. Am. Chem. Soc. 2021, 143, 2857-65.

199. Zhang, Z.; Li, H.; Shao, Y.; et al. Molecular understanding of the critical role of alkali metal cations in initiating CO2 electroreduction on Cu(100) surface. Nat. Commun. 2024, 15, 612.

200. Yang, X.; Ding, H.; Li, S.; Zheng, S.; Li, J. F.; Pan, F. Cation-induced interfacial hydrophobic microenvironment promotes the C-C coupling in electrochemical CO2 reduction. J. Am. Chem. Soc. 2024, 146, 5532-42.

201. Ringe, S.; Clark, E. L.; Resasco, J.; et al. Understanding cation effects in electrochemical CO2 reduction. Energy. Environ. Sci. 2019, 12, 3001-14.

202. Gu, J.; Liu, S.; Ni, W.; Ren, W.; Haussener, S.; Hu, X. Modulating electric field distribution by alkali cations for CO2 electroreduction in strongly acidic medium. Nat. Catal. 2022, 5, 268-76.

203. Marcandalli, G.; Goyal, A.; Koper, M. T. M. Electrolyte effects on the Faradaic efficiency of CO2 reduction to CO on a gold electrode. ACS. Catal. 2021, 11, 4936-45.

204. Liu, X.; Schlexer, P.; Xiao, J.; et al. pH effects on the electrochemical reduction of CO(2) towards C(2) products on stepped copper. Nat. Commun. 2019, 10, 32.

205. Kastlunger, G.; Heenen, H. H.; Govindarajan, N. Combining first-principles kinetics and experimental data to establish guidelines for product selectivity in electrochemical CO2 reduction. ACS. Catal. 2023, 13, 5062-72.

206. Lee, T.; Lee, Y.; Eo, J.; Nam, D. H. Acidic CO2 electroreduction for high CO2 utilization: catalysts, electrodes, and electrolyzers. Nanoscale 2024, 16, 2235-49.

207. Hicks, M. H.; Nie, W.; Boehme, A. E.; Atwater, H. A.; Agapie, T.; Peters, J. C. Electrochemical CO2 reduction in acidic electrolytes: spectroscopic evidence for local pH gradients. J. Am. Chem. Soc. 2024, 146, 25282-9.

208. Fan, M.; Huang, J. E.; Miao, R. K.; et al. Cationic-group-functionalized electrocatalysts enable stable acidic CO2 electrolysis. Nat. Catal. 2023, 6, 763-72.

209. Huang, J. E.; Li, F.; Ozden, A.; et al. CO2 electrolysis to multicarbon products in strong acid. Science 2021, 372, 1074-8.

210. Monteiro, M. C. O.; Philips, M. F.; Schouten, K. J. P.; Koper, M. T. M. Efficiency and selectivity of CO2 reduction to CO on gold gas diffusion electrodes in acidic media. Nat. Commun. 2021, 12, 4943.

211. Xie, Y.; Ou, P.; Wang, X.; et al. High carbon utilization in CO2 reduction to multi-carbon products in acidic media. Nat. Catal. 2022, 5, 564-70.

212. Henkelman, G.; Uberuaga, B. P.; Jónsson, H. A climbing image nudged elastic band method for finding saddle points and minimum energy paths. J. Chem. Phys. 2000, 113, 9901-4.

213. Henkelman, G.; Jónsson, H. A dimer method for finding saddle points on high dimensional potential surfaces using only first derivatives. J. Chem. Phys. 1999, 111, 7010-22.

214. Mathew, K.; Sundararaman, R.; Letchworth-Weaver, K.; Arias, T. A.; Hennig, R. G. Implicit solvation model for density-functional study of nanocrystal surfaces and reaction pathways. J. Chem. Phys. 2014, 140, 084106.

215. Bramley, G.; Nguyen, M. T.; Glezakou, V. A.; Rousseau, R.; Skylaris, C. K. Reconciling work functions and adsorption enthalpies for implicit solvent models: a Pt (111)/water interface case study. J. Chem. Theory. Comput. 2020, 16, 2703-15.

216. Hörmann, N. G.; Guo, Z.; Ambrosio, F.; Andreussi, O.; Pasquarello, A.; Marzari, N. Absolute band alignment at semiconductor-water interfaces using explicit and implicit descriptions for liquid water. npj. Comput. Mater. 2019, 5, 238.

217. Islam, S. M. R.; Khezeli, F.; Ringe, S.; Plaisance, C. An implicit electrolyte model for plane wave density functional theory exhibiting nonlinear response and a nonlocal cavity definition. J. Chem. Phys. 2023, 159, 234117.

218. Perego, S.; Bonati, L. Data efficient machine learning potentials for modeling catalytic reactivity via active learning and enhanced sampling. npj. Comput. Mater. 2024, 10, 1481.

219. Ding, R.; Chen, J.; Chen, Y.; Liu, J.; Bando, Y.; Wang, X. Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation. Chem. Soc. Rev. 2024, 53, 11390-461.

220. Mou, L. H.; Han, T.; Smith, P. E. S.; Sharman, E.; Jiang, J. Machine learning descriptors for data-driven catalysis study. Adv. Sci. 2023, 10, e2301020.

221. Song, Z.; Fan, L.; Lu, S.; Ling, C.; Zhou, Q.; Wang, J. Inverse design of promising electrocatalysts for CO2 reduction via generative models and bird swarm algorithm. Nat. Commun. 2025, 16, 1053.

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