教育经历
工作经历
研究
为各种模拟体系开发基于深度学习方法的势能，包括碳氢燃料燃烧、RNA催化反应、药物发现和精密医学。
发表文章
DPA-2: a large atomic model as a multi-task learner
Duo Zhang, Xinzijian Liu, Xiangyu Zhang, Chengqian Zhang, Chun Cai, Hangrui Bi, Yiming Du, Xuejian Qin, Anyang Peng, Jiameng Huang, Bowen Li, Yifan Shan, Jinzhe Zeng, Yuzhi Zhang, Siyuan Liu, Yifan Li, Junhan Chang, Xinyan Wang, Shuo Zhou, Jianchuan Liu, Xiaoshan Luo, Zhenyu Wang, Wanrun Jiang, Jing Wu, Yudi Yang, Jiyuan Yang, Manyi Yang, Fu-Qiang Gong, Linshuang Zhang, Mengchao Shi, Fu-Zhi Dai, Darrin M. York, Shi Liu, Tong Zhu, Zhicheng Zhong, Jian Lv, Jun Cheng, Weile Jia, Mohan Chen, Guolin Ke, Weinan E, Linfeng Zhang, Han Wang
npj Comput. Mater, 2024, 10 (1), 293.
DOI: 10.1038/s41524-024-01493-2
Software Infrastructure for Next-Generation QM/MM-$\Delta$MLP Force Fields
Timothy J. Giese, Jinzhe Zeng, Lauren Lerew, Erika McCarthy, Yujun Tao, \cS"olen Ekesan, Darrin M. York
J. Phys. Chem., B, 2024, 128 (26), 6257–6271.
DOI: 10.1021/acs.jpcb.4c01466
Amber free energy tools: Interoperable software for free energy simulations using generalized quantum mechanical/molecular mechanical and machine learning potentials
Yujun Tao, Timothy J. Giese, \cS"olen Ekesan, Jinzhe Zeng, B'alint Aradi, Ben Hourahine, Hasan Metin Aktulga, Andreas W. G"otz, Kenneth M. Merz Jr, Darrin M. York
J. Chem. Phys., 2024, 160 (22), 224104.
DOI: 10.1063/5.0211276
DeePMD-kit v2: A software package for deep potential models
Jinzhe Zeng, Duo Zhang, Denghui Lu, Pinghui Mo, Zeyu Li, Yixiao Chen, Mari'an Rynik, Li'ang Huang, Ziyao Li, Shaochen Shi, Yingze Wang, Haotian Ye, Ping Tuo, Jiabin Yang, Ye Ding, Yifan Li, Davide Tisi, Qiyu Zeng, Han Bao, Yu Xia, Jiameng Huang, Koki Muraoka, Yibo Wang, Junhan Chang, Fengbo Yuan, Sigbj\orn L\oland Bore, Chun Cai, Yinnian Lin, Bo Wang, Jiayan Xu, Jia-Xin Zhu, Chenxing Luo, Yuzhi Zhang, Rhys E A Goodall, Wenshuo Liang, Anurag Kumar Singh, Sikai Yao, Jingchao Zhang, Renata Wentzcovitch, Jiequn Han, Jie Liu, Weile Jia, Darrin M York, Weinan E, Roberto Car, Linfeng Zhang, Han Wang
J. Chem. Phys., 2023, 159, 54801.
DOI: 10.1063/5.0155600
Modern semiempirical electronic structure methods and machine learning potentials for drug discovery: Conformers, tautomers, and protonation states
Jinzhe Zeng, Yujun Tao, Timothy J Giese, Darrin M York
J. Chem. Phys., 2023, 158, 124110.
DOI: 10.1063/5.0139281
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