ArticleProceedings of the National Academy of Sciences of the United States of America2026
A multiscale theory framework predicts size- and ordering-dependent activity in Pt-Cu oxygen reduction reaction catalysts.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Optimizing the oxygen reduction reaction (ORR) performance of Pt-based alloy nanocatalysts requires a quantitative understanding of how catalytic activity and durability depend on nanoparticle composition, size, and atomic ordering. In this work, we present a multiscale theoretical framework that integrates density functional theory (DFT), machine-learning-accelerated cluster expansions, and kinetic and Metropolis Monte Carlo simulations to predict the structural evolution and ORR activity of octahedral Pt-Cu nanoparticles under acidic conditions. Our model captures the configurational complexity of experimentally relevant (4 to 10 nm) particles and reveals that disordered Pt
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