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We investigated oxygen reduction reaction (ORR) properties of Pt-containing compositionally complex alloy (Pt-CCA) single-crystal model catalyst surfaces to optimize dry-process synthesis conditions, that is, CCA compositions of less-noble alloying elements and their synthesis (annealing) temperatures. Using a machine-learning approach, we effectively navigated the large space of possible synthesis conditions to minimize the experimental workload. The ORR activity and durability of the Pt/CCA/Pt(111) model catalyst surfaces (synthesized through vacuum deposition on a Pt(111) substrate of nonequiatomic Cr–Mn–Fe–Co–Ni or Mn–Fe–Co–Ni alloy (111) lattice stacking layers, followed by a surface Pt(111) layer) depend upon the alloy composition and synthesis temperature: the model catalyst surfaces synthesized with specific combinations of these two parameters outperformed benchmark surfaces such as Pt/equiatomic Cr–Mn–Fe–Co–Ni/Pt(111) in terms of the ORR durability during potential-cycle loading. The outstanding ORR properties are attributed to the use of machine learning to predict synthesis conditions that are closely linked to the atomic-level surface microstructures that favor enhanced ORR properties. These microstructures enable the formation of a so-called “pseudo-core-shell-like structure”, i.e., surface Pt(111) underlaid with CCA(111) lattice stacking layers with atomically distributed active elements (Co and/or Ni) close to the surface that are beneficial for ORR property enhancements. This study demonstrates that not only the “high-entropy” effect of charged less-noble CCA elements but also the precise control of elemental distributions in the near-surface vicinity in the pristine state, resulting from optimized CCA compositions and synthesis temperatures, are the key factors to improve Pt-CCA catalyst material systems.

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  This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Applied Materials & Interfaces, copyright © 2025 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsami.4c22052.

Keyword: compositionally complex alloy, materials informatics, Catalysts, oxygen reduction reaction

Date published: 2025-04-16

Publisher: American Chemical Society (ACS)

Journal:

• ACS Applied Materials & Interfaces (ISSN: 19448244) vol. 17 issue. 15 p. 22557-22567

Funding:

• New Energy and Industrial Technology Development Organization 20001184-0
• Japan Society for the Promotion of Science JP21H01645
• Japan Society for the Promotion of Science JP23KJ0111

Manuscript type: Author's version (Accepted manuscript)

MDR DOI: https://doi.org/10.48505/nims.6093

First published URL: https://doi.org/10.1021/acsami.4c22052

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Updated at: 2026-02-14 22:06:22 +0900

Published on MDR: 2026-04-06 08:25:49 +0900