Effects of Segregation on the Catalytic Properties of AgAuCuPdPt High-Entropy Alloy for CO Reduction Reaction

Multicomponent alloys are promising catalysts for diverse chemical conversions, owing to the ability to tune their vast compositional space to maximize catalytic activity and product selectivity. However, elemental segregation, whereby the surface or grain boundaries of the material are enriched in a few elements, is a physically observed phenomenon in such alloys. Such segregation alters not only the composition but also the kinds of catalytically active sites present at the surface. Thus, elemental segregation, which can be achieved via various processing techniques, can be used as an additional knob in searching for alloy compositions that are both active and selective for a target chemical conversion. We demonstrate this using molecular simulations, machine learning, and Bayesian optimization to search for both random solid solution and "segregated" AgAuCuPdPt alloy compositions that are potentially active and selective for CO reduction reaction (CORR). Finally, we validate our findings by computing the reaction-free energy landscape for the CORR on the optimal alloy compositions via density functional theory calculations.