Jinzhe Zeng's Blog


Jinzhe Zeng


Work Experience


Develop deep learning potentials for simulations of different applications, including combustion of hydrocarbon fuels, RNA catalysis reactions, drug discovery, and precision medicine.


Learning DeePMD-Kit: A Guide to Building Deep Potential Models

Wenshuo Liang, Jinzhe Zeng, Darrin M. York, Linfeng Zhang, Han Wang
A Practical Guide to Recent Advances in Multiscale Modeling and Simulation of Biomolecules, 2023, 6-1–6-20.
DOI: 10.1063/9780735425279_006

QD$\pi$: A Quantum Deep Potential Interaction Model for Drug Discovery

Jinzhe Zeng, Yujun Tao, Timothy J Giese, Darrin M York
J. Chem. Theory Comput., 2023.
DOI: 10.1021/acs.jctc.2c01172

Multireference Generalization of the Weighted Thermodynamic Perturbation Method

Timothy J Giese, Jinzhe Zeng, Darrin M York
J. Phys. Chem. A, 2022, 8519–8533.
DOI: 10.1021/acs.jpca.2c06201

Chapter 12 - Neural network potentials

Jinzhe Zeng, Liqun Cao, Tong Zhu
Quantum Chemistry in the Age of Machine Learning, 2023, 279-294.
DOI: 10.1016/B978-0-323-90049-2.00001-9

Combined QM/MM, Machine Learning Path Integral Approach to Compute Free Energy Profiles and Kinetic Isotope Effects in RNA Cleavage Reactions

Timothy J. Giese, Jinzhe Zeng, Şölen Ekesan, Darrin M. York
Journal of Chemical Theory and Computation, 2022, 18, 4304–4317.
DOI: 10.1021/acs.jctc.2c00151

Ab Initio Neural Network MD Simulation of Thermal Decomposition of High Energy Material CL-20/TNT

Liqun Cao, Jinzhe Zeng, Bo Wang, Tong Zhu, John Z.H. Zhang
Physical Chemistry Chemical Physics, 2022, 24, 11801–11811.
DOI: 10.1039/D2CP00710J

Development of Range-Corrected Deep Learning Potentials for Fast, Accurate Quantum Mechanical/molecular Mechanical Simulations of Chemical Reactions in Solution

Jinzhe Zeng, Timothy J. Giese, ̧Sölen Ekesan, Darrin M. York
Journal of Chemical Theory and Computation, 2021, 17 (11), 6993–7009.
DOI: 10.1021/acs.jctc.1c00201

Fragment-based Ab Initio Molecular Dynamics Simulation for Combustion

Liqun Cao, Jinzhe Zeng, Mingyuan Xu, Chih-Hao Chin, Tong Zhu, John ZH Zhang
Molecules, 2021, 26 (11), 3120.
DOI: 10.3390/molecules26113120

Exploring the Chemical Space of Linear Alkane Pyrolysis via Deep Potential GENerator

Jinzhe Zeng, Linfeng Zhang, Han Wang, Tong Zhu
Energy & Fuels, 2021, 35 (1), 762–769.
DOI: 10.1021/acs.energyfuels.0c03211

Complex reaction processes in combustion unraveled by neural network-based molecular dynamics simulation

Jinzhe Zeng, Liqun Cao, Mingyuan Xu, Tong Zhu, John Z. H. Zhang
Nature Communications, 2020, 11, 5713.
DOI: 10.1038/s41467-020-19497-z

DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models

Yuzhi Zhang, Haidi Wang, Weijie Chen, Jinzhe Zeng, Linfeng Zhang, Han Wang, Weinan E
Computer Physics Communnications, 2020, 253, 107206.
DOI: 10.1016/j.cpc.2020.107206

ReacNetGenerator: an automatic reaction network generator for reactive molecular dynamics simulations

Jinzhe Zeng, Liqun Cao, Chih-Hao Chin, Haisheng Ren, John Z. H. Zhang, Tong Zhu
Physical Chemistry Chemical Physics, 2020, 22 (2), 683–691.
DOI: 10.1039/C9CP05091D

Understanding the selectivity of inhibitors toward PI4KIII$\alpha$ and PI4KIII$\beta$ based molecular modeling

Shuaizhen Tian, Jinzhe Zeng, Xiao Liu, Jianzhong Chen, John ZH Zhang, Tong Zhu
Physical Chemistry Chemical Physics, 2019, 21 (39), 22103–22112.
DOI: 10.1039/C9CP03598B

Inorganic-Organic Hybrid Tongue-Mimic for Time-Resolved Luminescent Noninvasive Pattern and Chiral Recognition of Thiols in Biofluids toward Healthcare Monitoring

Xin-Yue Han, Zi-Han Chen, Jin-Zhe Zeng, Qian-Xi Fan, Zheng-Qi Fang, Guoyue Shi, Min Zhang
ACS Applied Materials & Interfaces, 2018, 10 (37), 31725–31734.
DOI: 10.1021/acsami.8b13498