王锋

参与国家自然科学基金重大项目“全固态电池表界面化学基础研究”

基于机器学习分子动力学解析电池电解液体相、界面电化学过程。

[1] Feng Wang, Zebing Ma, Jun Cheng. Accelerating Computation of Acidity Constants and Redox Potentials for Aqueous Organic Redox Flow Batteries by Machine Learning Potential-Based Molecular Dynamics. J. Am. Chem. Soc. 2024, 146, 14566-14575.

[2] Feng Wang, Yan Sun, Jun Cheng*, Level Switching Mechanism for Electrochemical Stability Improvement in Water-in-Salt Electrolytes. J. Am. Chem. Soc. 2023, 145, 4056−4064.

[3] Feng Wang, Jun Cheng*, Unraveling Origin of Reductive Stability of Super-concentrated Electrolytes from First Principles and Unsupervised Machine Learning. Chem. Sci. 2022, 13, 11570-11576.

[4] Feng Wang, Jun Cheng. Automated Workflow for Computation of Redox Potentials, Acidity Constants and Solvation Free Energies Accelerated by Machine Learning. J. Chem. Phys. 2022. 157, 024103.

[5] Feng Wang, Jun Cheng*, Understanding the solvation structures of glyme-based electrolytes by machine learning molecular dynamics. Chinese J. Struct. Chem. 2023, 100061.