陳文恺 博士，副教授，碩士生導師

電子郵件：wenkaichen@hebtu.edu.cn

科研室：理科群7号樓B-404

歡迎對結構化學、物理化學、理論計算化學、光化學、機器學習、程序編寫等方面感興趣的同學報考本組化學專業、材料與化工專業的研究生！

學習經曆：

2013.09-2017.06 北京師範大學 理學學士

2017.09-2022.06 北京師範大學 理學博士

工作經曆：

2022.07-至今 韦德体育官方网站 曆任講師、副教授

主講課程：

《結構化學》、《計算化學實驗》

研究領域：

理論及計算光化學。具體的研究方向為：（1）基于低标度電子結構方法和機器學習技術的非絕熱動力學模拟方案；（2）分子體系和周期性體系光物理過程的理論研究；（3）基于大數據和機器學習探索催化劑與催化活性間的構效關系。

科研項目：

國家自然科學基金青年科學基金(22303025)

河北省自然科學基金青年科學基金(B2023205003)

河北省高等學校科學技術研究項目-青年基金項目(QN2023176)

韦德体育官方网站科技類博士基金(L2023B12)

代表性論著：

(1)Wen-Kai Chen, Xiang-Yang Liu, Wei-Hai Fang, Pavlo O. Dral, Ganglong Cui*;Deep Learning for Nonadiabatic Excited-State Dynamics, J. Phys. Chem. Lett.,2018, 9, 6702-6708.

(2)Wen-Kai Chen, Wei-Hai Fang, Ganglong Cui*; IntegratingMachine Learning with the Multilayer Energy-Based Fragment Method for ExcitedStates of Large Systems, J. Phys. Chem. Lett., 2019,10, 7836-7841.

(3)Wen-Kai Chen, Wei-Hai Fang, Ganglong Cui*; A Multi-LayerEnergy-Based Fragment Method for Excited States and Nonadiabatic Dynamics, Phys.Chem. Chem. Phys., 2019, 21, 22695-22699.

(4)Wen-Kai Chen, Yaolong Zhang, Bin Jiang, Wei-Hai Fang, Ganglong Cui*;Efficient Construction of Excited-State Hessian Matrices with Machine LearningAccelerated Multilayer Energy-Based Fragment Method, J. Phys. Chem. A, 2020,124, 5684-5695.

(5)Wen-Kai Chen, Wei-Hai Fang, Ganglong Cui*; ExtendingMulti-Layer Energy-Based Fragment Method for Excited-State Calculations ofLarge Covalently Bonded Fragment Systems, J. Chem. Phys., 2023,158, 044110.

(6)Wen-Kai Chen, Sheng-Rui Wang, Xiang-Yang Liu, Wei-Hai Fang, Ganglong Cui*;Nonadiabatic Derivative Couplings Calculated Using Information of PotentialEnergy Surfaces without Wavefunctions: Ab Initio and Machine LearningImplementations, Molecules, 2023, 28, 4222.

(7)Yanjiang Wang, Chang Zhao, Wen-Kai Chen*, Yanli Zeng*;Chalcogen Bond Catalysis with Telluronium Cations for Bromination Reaction:Importance of Electrostatic and Polarization Effects, Chem. Eur. J., 2023,29, e202302749.

(8) Wen-Kai Chen, Xiang-Yang Liu,Ganglong Cui*; Generalized Trajectory-Based Surface-Hopping (GTSH)Nonadiabatic Dynamics with Time-Dependent Density Functional Theory:Methodologies and Applications. In Time-Dependent Density Functional Theory;Jenny Stanford Publishing: New York, 2022; pp 199–250. (書籍章節)