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
Automating Computational Chemistry Workflows via OpenClaw and Domain-Specific Skills
Mingwei Ding, Chen Huang, Yibo Hu, Yifan Li, Zitian Lu, Xingtai Yu, Duo Zhang, Wenxi Zhai, Tong Zhu, Qiangqiang Gu, Jinzhe Zeng
arXiv, 2026, 2603.25522.
DOI: 10.48550/arXiv.2603.25522
Bohrium + SciMaster: Building the Infrastructure and Ecosystem for Agentic Science at Scale
Linfeng Zhang, Siheng Chen, Yuzhu Cai, Jingyi Chai, Junhan Chang, Kun Chen, Zhi X. Chen, Zhaohan Ding, Yuwen Du, Yuanpeng Gao, Yuanpeng Gao, Jing Gao, Zhifeng Gao, Qiangqiang Gu, Yanhui Hong, Yuan Huang, Xi Fang, Xiaohong Ji, Guolin Ke, Zixing Lei, Xinyu Li, Yonggen Li, Ruo- tong Liao, Hang Lin, Xiaolu Lin, Yuxiang Liu, Xinzijian Liu, Zexi Liu, Jintan Lu, Tingjia Miao, Haohui Que, Weijie Sun, Yanfeng Wang, Bingyang Wu, Tianju Xue, Rui Ye, Jinzhe Zeng, Duoxiao Zhang, Jiahui Zhang, Tianhan Zhang, Wenchang Zhang, Yuzhi Zhang, Zezhong Zhang, Hang Zheng, Hui Zhou, Tong Zhu, Xinyu Zhu, Qin Zhou, E. Weinan
Arxiv, 2025.
DOI: 10.48550/arXiv.2512.20469
DPDispatcher: Scalable HPC Task Scheduling for AI-Driven Science
Fengbo Yuan, Zhaohan Ding, Yun-Pei Liu, Kai Cao, Jiahao Fan, Cao Thang Nguyen, Yuzhi Zhang, Haidi Wang, Yixiao Chen, Jiameng Huang, Tongqi Wen, Mingkang Liu, Yifan Li, Yong-Bin Zhuang, Hao Yu, Ping Tuo, Yaotang Zhang, Yibo Wang, Linfeng Zhang, Han Wang, Jinzhe Zeng
J. Chem. Inf. Model., 2025, 65 (22), 12155–12160.
DOI: 10.1021/acs.jcim.5c02081
dpdata: A Scalable Python Toolkit for Atomistic Machine Learning Data Sets
Jinzhe Zeng, Xingliang Peng, Yong-Bin Zhuang, Haidi Wang, Fengbo Yuan, Duo Zhang, Renxi Liu, Yingze Wang, Ping Tuo, Yuzhi Zhang, Yixiao Chen, Yifan Li, Cao Thang Nguyen, Jiameng Huang, Anyang Peng, Mari'an Rynik, Wei-Hong Xu, Zezhong Zhang, Xu-Yuan Zhou, Tao Chen, Jiahao Fan, Wanrun Jiang, Bowen Li, Denan Li, Haoxi Li, Wenshuo Liang, Ruihao Liao, Liping Liu, Chenxing Luo, Logan Ward, Kaiwei Wan, Junjie Wang, Pan Xiang, Chengqian Zhang, Jinchao Zhang, Rui Zhou, Jia-Xin Zhu, Linfeng Zhang, Han Wang
J. Chem. Inf. Model., 2025, 65 (21), 11497–11504.
DOI: 10.1021/acs.jcim.5c01767
Recent Developments in Amber Biomolecular Simulations
David A. Case, David S. Cerutti, Vin'\icius Wilian D. Cruzeiro, Thomas A. Darden, Robert E. Duke, Mahdieh Ghazimirsaeed, George M. Giamba\csu, Timothy J. Giese, Andreas W. G"otz, Julie A. Harris, Koushik Kasavajhala, Tai-Sung Lee, Zhen Li, Charles Lin, Jian Liu, Yinglong Miao, Romelia Salomon-Ferrrer, Jana Shen, Ryan Snyder, Jason Swails, Ross C. Walker, Jinan Wang, Xiongwu Wu, Jinzhe Zeng, Thomas E. Cheatham Iii, Daniel R. Roe, Adrian Roitberg, Carlos Simmerling, Darrin M. York, Maria C. Nagan, Kenneth M. Merz Jr
J. Chem. Inf. Model., 2025, 65 (15), 7835–7843.
DOI: 10.1021/acs.jcim.5c01063
DeePaTB: A deep learning powerd semi-empirical quantum mechanical method
Jin Xiao, Yingfeng Zhang, Bowen Li, Jinzhe Zeng, John Z. H. Zhang, Tong Zhu
ChemRxiv, 2025.
DOI: 10.26434/chemrxiv-2025-554jt
From Electronic Structure to Ion Transport: Photoelectron Spectroscopy and Molecular Dynamics Simulations Reveal the Role of Anions in Lithium Battery Electrolytes
Yanrong Jiang, Wenjin Cao, Xiao-Fei Gao, Jinzhe Zeng, Haoyu Cao, Shunwei Zhu, Wenhao Wang, Xue Cheng, Dongqin Sun, Feiyu Chen, Weijia Zhang, Zhubin Hu, Xue-Bin Wang
J. Phys. Chem., A, 2025, 129 (28), 6374–6384.
DOI: 10.1021/acs.jpca.5c03415
A Graph Neural Network for the Era of Large Atomistic Models
Duo Zhang, Anyang Peng, Chun Cai, Wentao Li, Yuanchang Zhou, Jinzhe Zeng, Mingyu Guo, Chengqian Zhang, Bowen Li, Hong Jiang, Tong Zhu, Weile Jia, Linfeng Zhang, Han Wang
arXiv, 2025, 2506.01686.
DOI: 10.48550/arXiv.2506.01686
Transferability of MACE Graph Neural Network for Range Corrected $\Delta$-Machine Learning Potential QM/MM Applications
Timothy J. Giese, Jinzhe Zeng, Darrin M. York
J. Phys. Chem., B, 2025, 129 (22), 5477–5490.
DOI: 10.1021/acs.jpcb.5c02006
Scaling Neural-Network-Based Molecular Dynamics with Long-Range Electrostatic Interactions to 51 Nanoseconds per Day
Jianxiong Li, Beining Zhang, Mingzhen Li, Siyu Hu, Jinzhe Zeng, Lijun Liu, Guojun Yuan, Zhan Wang, Guangming Tan, Weile Jia
Arxiv, 2025.
DOI: 10.48550/arXiv.2504.15508
DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials
Jinzhe Zeng, Duo Zhang, Anyang Peng, Xiangyu Zhang, Sensen He, Yan Wang, Xinzijian Liu, Hangrui Bi, Yifan Li, Chun Cai, Chengqian Zhang, Yiming Du, Jia-Xin Zhu, Pinghui Mo, Zhengtao Huang, Qiyu Zeng, Shaochen Shi, Xuejian Qin, Zhaoxi Yu, Chenxing Luo, Ye Ding, Yun-Pei Liu, Ruosong Shi, Zhenyu Wang, Sigbj\orn L\oland Bore, Junhan Chang, Zhe Deng, Zhaohan Ding, Siyuan Han, Wanrun Jiang, Guolin Ke, Zhaoqing Liu, Denghui Lu, Koki Muraoka, Hananeh Oliaei, Anurag Kumar Singh, Haohui Que, Weihong Xu, Zhangmancang Xu, Yong-Bin Zhuang, Jiayu Dai, Timothy J. Giese, Weile Jia, Ben Xu, Darrin M. York, Linfeng Zhang, Han Wang
J. Chem. Theory Comput., 2025, 21 (9), 4375–4385.
DOI: 10.1021/acs.jctc.5c00340
The QD$\pi$ dataset, training data for drug-like molecules and biopolymer fragments and their interactions
Jinzhe Zeng, Timothy J. Giese, Andreas W. G"otz, Darrin M. York
Sci. Data, 2025, 12 (1), 693.
DOI: 10.1038/s41597-025-04972-3
DeePMD-GNN: A DeePMD-kit Plugin for External Graph Neural Network Potentials
Jinzhe Zeng, Timothy J. Giese, Duo Zhang, Han Wang, Darrin M. York
J. Chem. Inf. Model., 2025, 65 (7), 3154–3160.
DOI: 10.1021/acs.jcim.4c02441
Development of Machine Learning Potentials for Biochemical Systems
Jinzhe Zeng
2025.
DOI: 10.7282/t3-1f9w-zs08
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
Dflow, a Python framework for constructing cloud-native AI-for-Science workflows
Xinzijian Liu, Yanbo Han, Zhuoyuan Li, Jiahao Fan, Chengqian Zhang, Jinzhe Zeng, Yifan Shan, Yannan Yuan, Wei-Hong Xu, Yun-Pei Liu, Yuzhi Zhang, Tongqi Wen, Darrin M. York, Zhicheng Zhong, Hang Zheng, Jun Cheng, Linfeng Zhang, Han Wang
arXiv, 2024, 2404.18392.
DOI: 10.48550/arXiv.2404.18392
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 (5), 054801.
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, 19, 1261–1275.
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, 126, 8519–8533.
DOI: 10.1021/acs.jpca.2c06201
Neural network potentials
Jinzhe Zeng, Liqun Cao, Tong Zhu
Quantum Chemistry in the Age of Machine Learning, 2022, 279–294.
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, \cS"olen Ekesan, Darrin M York
J. Chem. Theory Comput., 2022, 18, 4304–4317.
DOI: 10.1021/acs.jctc.2c00151
Ab initio neural network MD simulation of thermal decomposition of a high energy material CL-20/TNT
Liqun Cao, Jinzhe Zeng, Bo Wang, Tong Zhu, John Z. H. Zhang
Phys. Chem. Chem. Phys., 2022, 24 (19), 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, \cS"olen Ekesan, Darrin M. York
J. Chem. Theory Comput., 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 Z. H. Zhang
Mol. (Basel Switz.), 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
Nat. Commun., 2020, 11 (1), 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, Wang Han, Weinan E
Comput. Phys. Commun., 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
Phys. Chem. Chem. Phys., 2020, 22, 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 Z. H. Zhang, Tong Zhu
Phys. Chem. Chem. Phys., 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 Appl. Mater. Interfaces, 2018, 10 (37), 31725–31734.
DOI: 10.1021/acsami.8b13498