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Structure-Based Reaction Descriptors for Predicting Rate Constants by Machine Learning: Application to Hydrogen Abstraction from Alkanes by CH3/H/O Radicals

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成果类型:
期刊论文
作者:
Zhang, Yu;Yu, Jinhui;Song, Hongwei*;Yang, Minghui
通讯作者:
Song, Hongwei;Yang, MH
作者机构:
[Zhang, Yu] Huazhong Normal Univ, Coll Phys Sci & Technol, Wuhan 430079, Peoples R China.
[Yang, Minghui; Yu, Jinhui; Song, Hongwei; Zhang, Yu; Yang, MH] Chinese Acad Sci, Natl Ctr Magnet Resonance Wuhan, Innovat Acad Precis Measurement Sci & Technol, Key Lab Magnet Resonance Biol Syst,State Key Lab M, Wuhan 430071, Peoples R China.
[Yu, Jinhui] Chinese Acad Sci, Key Lab Plant Germplasm Enhancement & Specialty A, Wuhan Bot Garden, Wuhan 430074, Peoples R China.
[Yang, Minghui; Yang, MH] Huazhong Univ Sci & Technol, Wuhan Natl Lab Optoelect, Wuhan 430074, Peoples R China.
通讯机构:
[Song, HW; Yang, MH ] C
Chinese Acad Sci, Natl Ctr Magnet Resonance Wuhan, Innovat Acad Precis Measurement Sci & Technol, Key Lab Magnet Resonance Biol Syst,State Key Lab M, Wuhan 430071, Peoples R China.
Huazhong Univ Sci & Technol, Wuhan Natl Lab Optoelect, Wuhan 430074, Peoples R China.
语种:
英文
期刊:
Journal of Chemical Information and Modeling
ISSN:
1549-9596
年:
2023
卷:
63
期:
16
页码:
5097-5106
基金类别:
National Natural Science Foundation of China [21973109, 21973108, 21921004]; National Natural Science Foundation of China
机构署名:
本校为第一机构
院系归属:
物理科学与技术学院
摘要:
Accurate determination of the thermal rate constants for combustion reactions is a highly challenging task, both experimentally and theoretically. Machine learning has been proven to be a powerful tool to predict reaction rate constants in recent years. In this work, three supervised machine learning algorithms, including XGB, FNN, and XGB-FNN, are used to develop quantitative structure-property relationship models for the estimation of the rate constants of hydrogen abstraction reactions from alkanes by the free radicals CH(3), H, and O. The molecular similarity based on Morgan molecular fing...

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