Evidence map›Paper›PMID 41438673›Full record

ReviewNational science review2025

Decoding heterogeneous electrocatalysts for acidic oxygen evolution: mechanisms, rational design and AI acceleration.

Xingen Lin, Wenjia Qu, Zihan Wang, Jianuo Liu, Cheng Qian, Lin Tian, Lingxiao Wang, Yu Zhang, Huang Zhou, Yafei Zhao and 1 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in National science review, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Xingen LinState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Wenjia QuTianjin Key Laboratory of Advanced Carbon and Electrochemical Energy Storage, School of Chemical Engineering and Technology, and Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin 300072, China.
Zihan WangState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Jianuo LiuState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Cheng QianState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Lin TianState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Lingxiao WangState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Yu ZhangState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Huang ZhouState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Yafei ZhaoState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.
Yuen WuState Key Laboratory of Precision and Intelligent Chemistry, School of Chemistry and Materials Science, University of Science and Technology of China, Hefei 230026, China.ORCID https://orcid.org/0000-0001-9524-2843

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Proton exchange membrane water electrolyzers (PEMWEs) are positioned as a transformative technology for renewable energy conversion and storage systems. The acidic oxygen evolution reaction (AOER), serving as the pivotal half-reaction governing overall efficiency, operational stability and system cost in water electrolysis, has become a focal point of contemporary electrochemical research. In this Review, we comprehensively summarize the recent advancements in both noble metal-based (Ir and Ru) and non-noble-metal-based (Mn and Co) heterogeneous electrocatalysts (HEs) for the AOER. The analysis commences with fundamental AOER mechanisms and the key factors that influence them, elucidating critical structure-activity relationships essential for rational catalyst engineering. Subsequently, we systematically evaluate state-of-the-art design strategies and corresponding breakthroughs in catalyst development, followed by a forward-looking perspective on the emergence and application of AI for science in the AOER. This review provides valuable guidance for the design of next-generation HEs for the AOER, ultimately aiming to bridge the gap between laboratory-scale achievements and industrial implementation of PEMWE technologies.

Indexed as

artificial intelligencedesign strategiesheterogeneous electrocatalystsmechanismsoxygen evolution reaction

Identifiers

PMID41438673
PMCPMC12721389

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.