Han Wang

ResearcherID ORCID

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 9

Top Topics

Particulate Matter

Density Functional Theory

Top Venues

The Journal of chemical physics

The journal of physical chemistry. A

Journal of chemical theory and computation

Nature communications

This page only lists publications with an associated author ORCID identifier.

Publications

Xiaoyang Wang, Zhenyu Wang, Pengyue Gao, Chengqian Zhang, Jian Lv, Han Wang, Haifeng Liu, Yanchao Wang, Yanming Ma
Data-driven prediction of complex crystal structures of dense lithium. Nature communications 14 (1) (2023)
Wenfei Li, Qi Ou, Yixiao Chen, Yu Cao, Renxi Liu, Chunyi Zhang, Daye Zheng, Chun Cai, Xifan Wu, Han Wang, Mohan Chen, Linfeng Zhang
DeePKS + ABACUS as a Bridge between Expensive Quantum Mechanical Models and Machine Learning Potentials. The journal of physical chemistry. A (2022)
Denghui Lu, Wanrun Jiang, Yixiao Chen, Linfeng Zhang, Weile Jia, Han Wang, Mohan Chen
DP Compress: A Model Compression Scheme for Generating Efficient Deep Potential Models. Journal of chemical theory and computation 18 (9) (2022)
Yixiao Chen, Linfeng Zhang, Han Wang, Weinan E
Ground State Energy Functional with Hartree-Fock Efficiency and Chemical Accuracy. The journal of physical chemistry. A 124 (35) (2020)
Yixiao Chen, Linfeng Zhang, Han Wang, Weinan E
DeePKS: A Comprehensive Data-Driven Approach toward Chemically Accurate Density Functional Theory. Journal of chemical theory and computation 17 (1) (2020)
Han Wang, Jun Fang, Xingyu Gao
The optimal particle-mesh interpolation basis. The Journal of chemical physics 147 (12) (2018)
Linfeng Zhang, Han Wang, Weinan E
Adaptive coupling of a deep neural network potential to a classical force field. The Journal of chemical physics 149 (15) (2018)
Linfeng Zhang, Han Wang, Weinan E
Reinforced dynamics for enhanced sampling in large atomic and molecular systems. The Journal of chemical physics 148 (12) (2018)
Linfeng Zhang, Jiequn Han, Han Wang, Roberto Car, Weinan E
DeePCG: Constructing coarse-grained models via deep neural networks. The Journal of chemical physics 149 (3) (2018)