Elucidating the fundamental governing principles of CO 2 reduction on single-atom catalysts through interpretable machine learning

Journal of Materials Chemistry A 2026

View at publisher

Authors: Zhiheng Ji, Anjie Chen, Jinxin Sun, Peng Zhou, Jiarui Wang, Xiaojing Yao, Li Shi, Xiuyun Zhang

DOI: 10.1039/d5ta10584f

Cited by: 3

References: 63

Abstract

A universal atomic descriptor is proposed to accurately predict CO 2 RR thermodynamics on BC 2 -supported single-atom catalysts.

CO2 Reduction Techniques and Catalysts Machine Learning in Materials Science Electrocatalysts for Energy Conversion

References 63