Machine-learning-assisted high-throughput screening for accelerating the discovery of diatomic catalysts in N <sub>2</sub> electroreduction

An ML–DFT integrated high-throughput screening framework for diatomic catalysts toward the nitrogen reduction reaction (NRR).

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Publication Details

Journal
Journal of Materials Chemistry A
Published
2026-01-01
DOI
https://doi.org/10.1039/d5ta08910g
Primary Topic
Ammonia Synthesis and Nitrogen Reduction
Type
article
Field-Weighted Citation Impact
0.00
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article

Machine-learning-assisted high-throughput screening for accelerating the discovery of diatomic catalysts in N 2 electroreduction

Xingxing Yu, Ju Rong, X. Zhang, Yanbing Wu et al.
Journal of Materials Chemistry A
Ammonia Synthesis and Nitrogen Reduction
article

Machine-learning-assisted high-throughput screening for accelerating the discovery of diatomic catalysts in N 2 electroreduction

Xingxing Yu, Ju Rong, X. Zhang, Yanbing Wu, Hanqing Li, Keyuan Chen, Li Ma, Jueyi Ye, Yongqiang Yang
article en

Abstract

An ML–DFT integrated high-throughput screening framework for diatomic catalysts toward the nitrogen reduction reaction (NRR).

Journal of Materials Chemistry AVol. 14(14)
Kunming University of Science and Technology (CN), Chinese Academy of Sciences (CN)
Responsible consumption and production
Openalex Percentile: Top 96%
Ammonia Synthesis and Nitrogen Reduction
DOISourceOpenAlex
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