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High-throughput screening of CO2 cycloaddition MOF catalyst with an explainable machine learning model

Xuefeng Bai Yi Li Yabo Xie Qiancheng Chen Xin Zhang Jian-Rong Li

绿色能源与环境（英文）2025，Vol.10Issue(1)：132-138,7.

绿色能源与环境（英文）2025，Vol.10Issue(1)：132-138,7.DOI:10.1016/j.gee.2024.01.010

High-throughput screening of CO2 cycloaddition MOF catalyst with an explainable machine learning model

Xuefeng Bai ¹Yi Li ¹Yabo Xie ¹Qiancheng Chen ¹Xin Zhang ¹Jian-Rong Li¹

作者信息

1. Beijing Key Laboratory for Green Catalysis and Separation and Department of Chemical Engineering,College of Materials Science & Engineering,Beijing University of Technology,Beijing,100124,China
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摘要

关键词

Metal-organic frameworks/High-throughput screening/Machine learning/Explainable model/CO2 cycloaddition

Key words

Metal-organic frameworks/High-throughput screening/Machine learning/Explainable model/CO2 cycloaddition

引用本文复制引用

Xuefeng Bai,Yi Li,Yabo Xie,Qiancheng Chen,Xin Zhang,Jian-Rong Li..High-throughput screening of CO2 cycloaddition MOF catalyst with an explainable machine learning model[J].绿色能源与环境（英文）,2025,10(1):132-138,7.

基金项目

We acknowledge financial support from the National Key Research and Development Program of China(2021YFB 3501501),the National Natural Science Foundation of China(No.22225803,22038001,22108007 and 22278011),Beijing Natural Science Foundation(No.Z230023),and Beijing Science and Technology Commission(No.Z211100004321001). （2021YFB 3501501）

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