Journal article Interpretable data-driven discovery of high-performance multielement metal oxide electrocatalysts for oxygen evolution reaction from a small hybrid dataset
Wenqin Peng (author) (Search by this author)
ORCID https://orcid.org/0009-0008-6114-7037 (unauthenticated)
ORCID ;
Shigenobu Hayashi (author) (Search by this author)
;
Abraham Castro Garcia (author) (Search by this author)
; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI ; ORCID SAMURAI
Interpretable data-driven discovery of high-performance multielement metal oxide electrocatalysts for oxygen evolution reaction from a small hybrid da.pdf
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Wenqin Peng, Shigenobu Hayashi, Abraham Castro Garcia, Lei Fang, Masaki Takeguchi, Yibin Xu, Ken Sakaushi. Interpretable data-driven discovery of high-performance multielement metal oxide electrocatalysts for oxygen evolution reaction from a small hybrid dataset. Science and Technology of Advanced Materials. 2026, 27 (1), 2713992. https://doi.org/10.1080/14686996.2026.2713992

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(abstract)

Interpretable data-driven discovery of high-performance multielement metal oxide electrocatalysts for oxygen evolution reaction from a small hybrid dataset.

Rights:

Keyword: Electrocatalysis, Oxygen evolution reaction, Data-driven approach

Date published: 2026-12-31

Publisher: Informa UK Limited

Journal:

  • Science and Technology of Advanced Materials (ISSN: 14686996) vol. 27 issue. 1 2713992

Funding:

  • GteX Program Japan JPMJGX23H2
  • JST COI-NEXT ‘Center for Advanced Battery Collaboration’ JPMJPF2016
  • Japan Science and Technology Agency JPMJAP2421
  • Churchill College, Cambridge
  • Cavendish Laboratory, the University of Cambridge
  • MEXT Program: Data Creation and Utilization-Type Material Research and Development Project JPMXP1122712807

Manuscript type: Publisher's version (Version of record)

MDR DOI:

First published URL: https://doi.org/10.1080/14686996.2026.2713992

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Updated at: 2026-08-24 10:33:12 +0900

Published on MDR: 2026-08-24 12:27:06 +0900

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