Machine Learning‐Guided Design of L12‐Type Pt‐Based High‐Entropy Intermetallic Compound for Electrocatalytic Hydrogen Evolution Article Swipe
Zhe Wang
,
Xi Chen
,
Ting Lin
,
Baokun Zhang
,
Kepeng Song
,
Lin Gu
,
Tomas Edvinsson
,
Hong Liu
,
Rafael B. Araujo
,
Xiaowen Yu
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/adma.202510424
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1002/adma.202510424
Rational design of high‐entropy intermetallic compounds (HEICs) remains challenging due to complex structure‐property relationships and the lack of predictive tools. Here, a data‐driven framework is presented to evaluate the hydrogen evolution reaction (HER) activity of L1 2 ‐type quinary Pt 3 M(4) HEICs, where M comprises any four elements from six 3 d transition metals (Cr, Mn, Fe, Co, Ni, Zn). Guided by the Pm‐3m space group, 15 distinct compositions with numerous microstates are designed. A deep neural network, trained on 453 computed datasets, predicts hydrogen adsorption energy (∆ E H* ) across 20 000 microstructures per composition, enabling statistical mapping of site‐specific performance. To capture the effect of local atomic environments, a novel statistical evaluation approach is introduced that quantifies the number of microstates falling within the optimal ∆ E H* range, advancing beyond conventional mean‐based evaluations. Among all candidates, Pt 3 (CrMnFeCo) emerges as the most promising HER catalyst, validated experimentally over a wide pH range. Further in‐depth data mining reveals that surface Co, Cr, and Fe optimize Pt‐Pt‐M sites, while subsurface Ni and Co modulate Pt‐Pt‐Pt interactions. This study establishes a new paradigm for HEIC catalyst design and deepens the mechanistic understanding of activity origin in complex multimetal systems.
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- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/adma.202510424
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/adma.202510424
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- 55
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Machine Learning‐Guided Design of L12‐Type Pt‐Based High‐Entropy Intermetallic Compound for Electrocatalytic Hydrogen EvolutionWork title
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articleOpenAlex work type
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enPrimary language
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2025Year of publication
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2025-10-15Full publication date if available
- Authors
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Zhe Wang, Xi Chen, Ting Lin, Baokun Zhang, Kepeng Song, Lin Gu, Tomas Edvinsson, Hong Liu, Rafael B. Araujo, Xiaowen YuList of authors in order
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https://doi.org/10.1002/adma.202510424Publisher landing page
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bronzeOpen access status per OpenAlex
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| publication_date | 2025-10-15 |
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