4.8 Article

Materials Screening by the Descriptor Gmax(η): The Free-Energy Span Model in Electrocatalysis

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ACS CATALYSIS
卷 -, 期 -, 页码 1740-1758

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AMER CHEMICAL SOC
DOI: 10.1021/acscatal.2c03997

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oxygen electrocatalysis; nitrogen reduction reaction; scaling relation; bifunctional index; descriptor-based approach; microkinetic modeling; multidimensional database; data-driven electrocatalysis

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In order to transition from fossil-based energy resources to renewables, electrode materials that do not contain precious noble metals are needed for efficient catalysis in fuel cells, batteries, and electrolyzers. Materials screening at minimal computational cost is a powerful method to evaluate potential electrode compositions based on heuristic concepts. The Gmax(eta) concept, based on the idea of the free-energy span model, has been proposed as a universal approach for the screening of electrocatalysts. It factors in overpotential and kinetic effects to analyze trends in an evacuation scheme of adsorption free energies.
To move from fossil-based energy resources to a society based on renewables, electrode materials free of precious noble metals are required to efficiently catalyze electrochemical processes in fuel cells, batteries, or electrolyzers. Materials screening operating at minimal computational cost is a powerful method to assess the performance of potential electrode compositions based on heuristic concepts. While the thermodynamic overpotential in combination with the volcano concept refers to the most popular descriptor-based analysis in the literature, this notion cannot reproduce experimental trends reasonably well. About two years ago, the concept of Gmax(eta), based on the idea of the free-energy span model, has been proposed as a universal approach for the screening of electrocatalysts. In contrast to other available descriptor-based methods, Gmax(eta) factors overpotential and kinetic effects by a dedicated evacuation scheme of adsorption free energies into an analysis of trends. In the present perspective, we discuss the application of Gmax(eta) to different electrocatalytic processes, including the oxygen evolution and reduction reactions, the nitrogen reduction reaction, and the selectivity problem of the competing oxygen evolution and peroxide formation reactions, and we outline the advantages of this screening approach over previous investigations.

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