Searching for an Optimal Multi‐Metallic Alloy Catalyst by Active Learning Combined with Experiments (Adv. Mater. 19/2022)

Hydrogen Evolution Reaction In article number 2108900, Won Bo Lee, YongJoo Kim, Hee‐tae Jung, and co‐workers report a methodology to efficiently search for optimal multi‐metallic alloy catalysts by combination of experiment and active learning. By this approach, it is possible to find a specific opt...

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Published inAdvanced materials (Weinheim) Vol. 34; no. 19
Main Authors Kim, Minki, Ha, Min Young, Jung, Woo‐Bin, Yoon, Jeesoo, Shin, Euichul, Kim, Il‐doo, Lee, Won Bo, Kim, YongJoo, Jung, Hee‐tae
Format Journal Article
LanguageEnglish
Published 12.05.2022
Subjects
active learning
carbothermal shock
catalyst composition
hydrogen evolution reaction
multi‐metallic catalysts
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Summary:Hydrogen Evolution Reaction In article number 2108900, Won Bo Lee, YongJoo Kim, Hee‐tae Jung, and co‐workers report a methodology to efficiently search for optimal multi‐metallic alloy catalysts by combination of experiment and active learning. By this approach, it is possible to find a specific optimal component and composition of catalyst for the hydrogen evolution reaction in the studied system. This method can be applied to any kind of reaction regardless of its own catalytic background.
ISSN:0935-9648
1521-4095
DOI:10.1002/adma.202270147