Dr. Sheng-Cai Zhu [School of Materials, Shenzhen Campus of Sun Yat-sen University, Shenzhen, China]

Title: From machine learning to materials simulation

Time: Monday (9:30-11:00), Jan 15th 2024

Place: Conference Room 410 HPSTAR SH

Online: https://meeting.tencent.com/dm/hlAD1AOZQ6T7

#Meeting ID：276-734-337

 Host: Dr. Qingyang Hu

Abstract

Atomic simulations based on quantum mechanics (QM) calculations have entered into the tool box of materials scientist in the past few decades, facilitating an understanding of a wide range of problems, from structures to properties. Due to the poor scaling and high computational cost intrinsic to QM calculations, one has to either sacrifice accuracy or time when performing large-scale atomic simulations. In recent years, Artificial Intelligence is widely used in the materials research field. As one of the application, machine-learning (ML)-based large-scale atomic simulations has shown great promise to the benefit of materials simulation. Instead of solving the Schrödinger equation directly, ML-based simulations rely on a large data set of accurate potential energy surfaces (PESs) and complex numerical models to predict the total energy. These simulations feature both a high speed and a high accuracy for computing large systems. In this seminar, I will talk about some application from machine learning potential from my group. Such as the graphite to hexagonal diamond under shock condition, the topological order transition in AlPO4 between crystal and amorphous, the potential energy surface search in Si-O-H, and the phase transition in perovskite solar materials.

Reference:

Chen Gu-wen, Xu Liang, Li Yao Min, Liu, Zhi-Pan, Zhu, Sheng-Cai. Strength-dependent Transition of Graphite Under Shock Condition Resolved by First Principles. arXiv preprint arXiv:2311.08805, 2023.(submitted)

Zhu Sheng-cai#*; Chen Gu-wen#; Zhang Dongzhou; Xu Liang; Liu Zhi-Pan; Mao Ho-kwang; Hu Qingyang*; Topological ordering of memory glass in extended length scales, J. Am. Chem. Soc., 2022, 144, 7414−7421.

Li Junwei, Lin Yanhao, Thomas Meier, Liu Zhipan, Yang Wei, Mao Ho-kwang, Zhu Sheng-cai*, Hu Qingyang*; Silica-water superstructure and one-dimensional superionic conduit in Earth’s mantle; Science Advances, 2023, 9, eadh3784.

Chen Tian, Xie Jiangsheng*, Wen Bin, Yin Qixin, Lin Ruohao, Zhu Sheng-cai*, Gao Pingqi*, Inhibition of defect-induced α-to-δ phase transition for efficient and stable formamidinium perovskite solar cells, Nature Communication, 2023, 14, 6125.