Application of machine learning and deep learning methods for hydrated electron rate constant prediction

Author:

Zheng Shanshan,Guo Wanqian,Li Chao,Sun Yongbin,Zhao Qi,Lu Hao,Si Qishi,Wang Huazhe

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Harbin Institute of Technology

State Key Laboratory of Urban Water Resource and Environment

Publisher

Elsevier BV

Subject

General Environmental Science,Biochemistry

Reference47 articles.

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2. Degradation of perfluoroalkyl ether carboxylic acids with hydrated electrons: structure–reactivity relationships and environmental implications;Bentel;Environ. Sci. Technol.,2020

3. Defluorination of per-and polyfluoroalkyl substances (PFASs) with hydrated electrons: structural dependence and implications to PFAS remediation and management;Bentel;Environ. Sci. Technol.,2019

4. QSPR prediction of the hydroxyl radical rate constant of water contaminants;Borhani;Water Res.,2016

5. Classification of Skin Lesions by Combining Multilevel Learnings in a DenseNet Architecture;Carcagnì,2019

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