The CatMath: an online predictive platform for thermal + electrocatalysis

Abstract

The catalytic volcano activity models are the quantified and visualized tools of the Sabatier principle for heterogeneous catalysis, which can depict the intrinsic activity optima and trends of a catalytic reaction as a function of the reaction descriptors, i.e., the bonding strengths of key reaction species. These models can be derived by microkinetic modeling and/or free energy changes in combination with the scaling relations among the reaction intermediates. Herein, we introduce the CatMath—an online platform for generating a variety of common and industrially important thermal + electrocatalysis. With the CatMath, users can request the volcano models for available reactions and analyze their materials of interests as potential catalysts. Besides, the CatMath provides the function of the online generation of Surface Pourbaix Diagram for surface state analysis under electrocatalytic conditions, which is an essential step before analyzing the activity of an electrocatalytic surface. All the model generation and analysis processes are realized by cloud computing via a user-friendly interface.

Graphical abstract

Keywords

CatMath / catalysis / volcano activity plots / Surface Pourbaix Diagrams / online platform

References

[1] Seh Z W, Kibsgaard J, Dickens C F, Chorkendorff I, Nørskov J K, Jaramillo T F. Combining theory and experiment in electrocatalysis: insights into materials design. Science, 2017, 355(6321): eaad4998

[2] Medford A J, Vojvodic A, Hummelshøj J S, Voss J, Abild-Pedersen F, Studt F, Bligaard T, Nilsson A, Nørskov J K. From the Sabatier principle to a predictive theory of transition-metal heterogeneous catalysis. Journal of Catalysis, 2015, 328: 36–42

[3] Medford A J, Moses P G, Jacobsen K W, Peterson A A. A career in catalysis: Jens Kehlet Nørskov. ACS Catalysis, 2022, 12(15): 9679–9689

[4] Hammer B, Nørskov J K. Theoretical surface science and catalysis—calculations and concepts. Advances in Catalysis, 2000, 45: 71–129

[5] Nørskov J K, Abild-Pedersen F, Studt F, Bligaard T. Density functional theory in surface chemistry and catalysis. Proceedings of the National Academy of Sciences of the United States of America, 2011, 108(3): 937–943

[6] Jones G, Bligaard T, Abild-Pedersen F, Nørskov J K. Using scaling relations to understand trends in the catalytic activity of transition metals. Journal of Physics Condensed Matter, 2008, 20(6): 064239

[7] Nørskov J K, Bligaard T, Logadottir A, Kitchin J R, Chen J G, Pandelov S, Stimming U. Trends in the exchange current for hydrogen evolution. Journal of the Electrochemical Society, 2005, 152(3): J23–J26

[8] Nørskov J K, Rossmeisl J, Logadottir A, Lindqvist L, Kitchin J R, Bligaard T, Jónsson H. Origin of the overpotential for oxygen reduction at a fuel-cell cathode. Journal of Physical Chemistry B, 2004, 108(46): 17886–17892

[9] Falsig H, Hvolbæk B, Kristensen I S, Jiang T, Bligaard T, Christensen C H, Nørskov J K. Trends in the catalytic CO oxidation activity of nanoparticles. Angewandte Chemie International Edition, 2008, 47(26): 4835–4839

[10] Dickens C F, Kirk C, Nørskov J K. Insights into the electrochemical oxygen evolution reaction with ab initio calculations and microkinetic modeling: beyond the limiting potential volcano. Journal of Physical Chemistry C, 2019, 123(31): 18960–18977

[11] Hansen H A, Varley J B, Peterson A A, Nørskov J K. Understanding trends in the electrocatalytic activity of metals and enzymes for CO₂ reduction to CO. Journal of Physical Chemistry Letters, 2013, 4(3): 388–392

[12] Pan S, Li H, Liu D, Huang R, Pan X, Ren D, Li J, Shakouri M, Zhang Q X, Wang M J. . Efficient and stable noble-metal-free catalyst for acidic water oxidation. Nature Communications, 2022, 13(1): 2294

[13] Man I C, Su H Y, Calle-Vallejo F, Hansen H A, Martínez J I, Inoglu N G, Kitchin J, Jaramillo T F, Nørskov J K, Rossmeisl J. Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem, 2011, 3(7): 1159–1165

[14] Liu H, Zhang D, Holmes S M, D’Agostino C, Li H. Origin of the superior oxygen reduction activity of zirconium nitride in alkaline media. Chemical Science, 2023, 14(34): 9000–9009

[15] Xu H, Zhu L, Nan Y, Xie Y, Cheng D. Revisit the role of metal dopants in enhancing the selectivity of Ag-catalyzed ethylene epoxidation: optimizing oxophilicity of reaction site via cocatalytic mechanism. ACS Catalysis, 2021, 11(6): 3371–3383

[16] Liu X, Xiao J, Peng H, Hong X, Chan K, Nørskov J K. Understanding trends in electrochemical carbon dioxide reduction rates. Nature Communications, 2017, 8(1): 15438

[17] Nørskov J K, Bligaard T, Rossmeisl J, Christensen C H. Towards the computational design of solid catalysts. Nature Chemistry, 2009, 1(1): 37–46

[18] Kelly S R, Kirk C, Chan K, Nørskov J K. Electric field effects in oxygen reduction kinetics: rationalizing pH dependence at the Pt(111), Au(111), and Au(100) Electrodes. Journal of Physical Chemistry C, 2020, 124(27): 14581–14591

[19] Medford A J, Shi C, Hoffmann M J, Lausche A C, Fitzgibbon S R, Bligaard T, Nørskov J K. CatMAP: a software package for descriptor-based microkinetic mapping of catalytic trends. Catalysis Letters, 2015, 145(3): 794–807

[20] Liu H, Jia X, Cao A, Wei L, D’Agostino C, Li H. The surface states of transition metal X-ides under electrocatalytic conditions. Journal of Chemical Physics, 2023, 158(12): 124705

[21] Hansen H A, Rossmeisl J, Nørskov J K. Surface Pourbaix diagrams and oxygen reduction activity of Pt, Ag and Ni(111) surfaces studied by DFT. Physical Chemistry Chemical Physics, 2008, 10(25): 3722–3730

[22] 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(41): 12259–12269

[23] Yang W, Jia Z, Zhou B, Wei L, Gao Z, Li H. Surface states of dual-atom catalysts should be considered for analysis of electrocatalytic activity. Communications Chemistry, 2023, 6(1): 6

Competing interests

The authors declare that they have no competing interests.

Acknowledgements

This work was funded by JSPS KAKENHI (Grant No. JP23K13703).

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11705-023-2371-3 and is accessible for authorized users.

Open Access

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

RIGHTS & PERMISSIONS

2023 The Author(s) 2023. This article is published with open access at link.springer.com and journal.hep.com.cn