A combined first-principles and data-driven computational framework to analyze the surface structure, composition, and stability of binary alloy catalysts

24 June 2024, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Pt-based bimetallic alloys are considerably more active than Pt for the oxygen reduction reaction (ORR). This increased activity has been attributed to weakening of the adsorption of ORR intermediates due to the presence of Pt “skins.” Density functional theory (DFT) calculations have, in turn, pointed to the importance of surface segregation energies and Pt leaching on the formation and stability of the skins on close-packed surfaces of Pt alloys. The generalizability of these insights across different chemical environments, surface compositions, and facets, however, remains a subject of active research and is the focus of this work. We present a generalized computational framework combining DFT calculations and data-driven methods to predict the stability of different Pt3X (X = Ni, Co, Fe, and Cu) alloy facets under vacuum conditions and in the presence of an electrochemical environment, wherein we analyze the combined effect of segregation, intrasurface phase separation, leaching, and surface oxidation as a function of electrode potential. The analysis reveals that a subtle interplay of these factors influences Pt skin formation and stability, with Pt segregation being a strong function of the surface structure, and continuous base metal dissolution being thermodynamically, although not always kinetically, favored at ORR-relevant voltages.

Keywords

Density Functional Theory
Surface Thermodynamics
Alloy Stability
PtNi
Oxygen Reduction Reaction

Supplementary materials

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Supporting Information
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This document contains supporting information including additional derivations, analyses, and surface phase diagrams. A detailed description of the machine learning workflow is also provided.
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