首页|期刊导航|含能材料前沿（英文）|Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis

Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis

Zhi-xiang Zhang Yi-lin Cao Chao Chen Lin-yuan Wen Yi-ding Ma Bo-zhou Wang Ying-zhe Liu

含能材料前沿（英文）2024，Vol.5Issue(4)：274-282,9.

含能材料前沿（英文）2024，Vol.5Issue(4)：274-282,9.DOI:10.1016/j.enmf.2023.09.004

Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis

Zhi-xiang Zhang ¹Yi-lin Cao ¹Chao Chen ¹Lin-yuan Wen ¹Yi-ding Ma ¹Bo-zhou Wang ²Ying-zhe Liu¹

作者信息

1. Xi'an Key Laboratory of Liquid Crystal and Organic Photovoltaic Materials,Xi'an Modern Chemistry Research Institute,Xi'an,710065,China||State Key Laboratory of Fluorine&Nitrogen Chemicals,Xi'an Modern Chemistry Research Institute,Xi'an,710065,China
2. State Key Laboratory of Fluorine&Nitrogen Chemicals,Xi'an Modern Chemistry Research Institute,Xi'an,710065,China
折叠

摘要

关键词

Energetic compound/Molecular descriptor/Thermal decomposition temperature/Machine learning/Feature analysis

Key words

Energetic compound/Molecular descriptor/Thermal decomposition temperature/Machine learning/Feature analysis

引用本文复制引用

Zhi-xiang Zhang,Yi-lin Cao,Chao Chen,Lin-yuan Wen,Yi-ding Ma,Bo-zhou Wang,Ying-zhe Liu..Machine learning-assisted quantitative prediction of thermal decomposition temperatures of energetic materials and their thermal stability analysis[J].含能材料前沿（英文）,2024,5(4):274-282,9.

基金项目

This work was supported by the Shaanxi Natural Science Foundation(Nos.:2023-JC-QN-0111,2022JC-10)and the National Natural Science Foundation of China(Nos.:22275145,21875184). （Nos.:2023-JC-QN-0111,2022JC-10）

含能材料前沿（英文）

访问量2

下载量0

段落导航