时间：2025年5月29日（星期四）下午14:00-15:30

Time: 14:00-15:30, Thursday, May 29, 2025

主持人：西湖大学理学院PI 刘仕

Host: Dr. Shi Liu, PI of School of Science, Westlake University

地点：云谷校区E10-215

Venue: E10-215, Yungu Campus, Westlake University

讲座语言：中文

Lecture Language: Chinese

Prof.Jian Sun,

National Laboratory of Solid State Microstructures and School of Physics, 

Nanjing University, Nanjing, 210093, China.

主讲人/Speaker:

Jian Sun is a professor at the School of Physics and National Laboratory of Solid State Microstructures at Nanjing University. He got his B.S. and Ph.D. from Nanjing University in 2002 and 2007, respectively. After that, he spent 6 years and worked as a research fellow at NRC (Canada), Ruhr University Bochum (Germany), and the University of Cambridge (UK). In 2013, he was recruited as a professor at Nanjing University. Professor Sun’s research interest mainly focus on computational condensed matter physics and high-pressure physics, material design, and deep planetary matter. He has developed several new computational simulation methods, including the machine learning and graph theory assisted crystal structure prediction method (MAGUS), message passing machine learning force fields (HotPP) and machine learning molecular dynamics software (GPUMD). He predicted a number of new materials, and several have been confirmed by experiments. He also predicts the novel states of matter such as superionic state and plastic crystalline state of systems at high temperature and high pressure. Prof. Sun has published more than 130 peer-reviewed papers in scientific journals, including more than 20 papers in Nature series/PRL/PNAS/JACS. He has received many prestigious honors, including the distinguished young scholar of NSFC (2021), the Van Valkenburg award (2014), the Humboldt fellowship, the Marie Curie fellowship, etc. Professor Sun is a committee member of the high pressure Physics branch of the Chinese Physics Society, the Computational Materials Science branch of the Chinese Materials Research Society, and the high pressure Chemistry branch of the Chinese Chemistry Society, and serve as the Associate Editor-in-Chief of Progress of Physics, the editor board member of Matter and Radiation at Extremes and Journal of High Pressure Physics.

讲座摘要/Abstract:

In this talk, I will introduce some machine learning based materials simulation methods developed or co-developed in my group, including the machine learning and graph theory assisted crystal structure prediction method (MAGUS) [1,2], the high order tensor massage passing interatomic machine learning potential (HotPP) [3], and the machine learning molecular dynamics engine GPUMD [4], and. In addition, I will show some of our recent progress in the applications of these methods to predict new compounds of different research fields [5-7], including planetary minerals and functional materials, such as superhard, high energy density, and superconducting materials, etc.

REFERENCE

1. Yu Han et al., “Efficient crystal structure prediction based on the symmetry principle”, Nature Computational Science 5, 255 (2025).

2. Junjie Wang et al., “MAGUS: machine learning and graph theory assisted universal structure searcher”, Natl. Sci. Rev., nwad128 (2023). https://gitlab.com/bigd4/magus

3. Junjie Wang et al., “E(n)-Equivariant Cartesian Tensor Message Passing Interatomic Potential”, Nature Commun. 15, 7607 (2024). https://gitlab.com/bigd4/hotpp

4. Zheyong Fan et al., “GPUMD: A package for constructing accurate machine-learned potentials and performing highly efficient atomistic simulations”, J. Chem. Phys. 157, 114801 (2022).

5. Shuning Pan et al., “Magnesium oxide-water compounds at megabar pressure and implications on planetary interiors”, Nature Commun. 14, 1165 (2023).

6. Hao Gao et al., “Superionic Silica-Water and Silica-Hydrogen Compounds in the Deep Interiors of Uranus and Neptune”, Phys. Rev. Lett. 128, 035702 (2022).

7. Jiuyang Shi et al., “Double-Shock Compression Pathways from Diamond to BC8 Carbon”, Phys. Rev. Lett. 131, 146101 (2023).

讲座联系人/Contact:

School of Science, Yanyan Chen, Email: chenyanyan@westlake.edu.cn