永利yl23411官网材料科学与工程研究院《材料科学论坛》学术报告
报告时间：2024年3月14日下午14:00-17:00
报告人：Dr. Shigenobu Ogata（Department of Mechanical Science and Bioengineering in Osaka University）
报告地点：永利yl23411官网逸夫技术科学楼B213
邀请人：林元华教授
Atomistic modeling of hydrogen impact on metals
报告简介：
The study of hydrogen's behavior and its impact on deformation and fracture in metals has been extensive, with numerous models and theories developed. However, direct observation of hydrogen in materials remains challenging, leaving many questions unanswered. Atomistic simulation emerges as a valuable tool for directly investigating hydrogen behaviors and their effects on deformation and fracture. The effectiveness of these simulations largely depends on accurately describing atomic interactions within the iron-hydrogen system. Recent advancements[1][2] include the proposal of artificial neural network (ANN) atomic interactions for the iron-hydrogen binary system, trained using a dataset based on Density Functional Theory (DFT) calculations of energy, force, and structure. These ANN atomic interactions combine the computational efficiency of empirical models with the accuracy and transferability of DFT, allowing for a quantitative elucidation of phenomena contributing to hydrogen embrittlement. This has led to a clearer understanding of how hydrogen influences vacancy movement[3], dislocation activities, and the mechanisms behind crack formation at both grain boundaries and within grains.
[1] Fan-Shun Meng, …, and Shigenobu Ogata, Physical Review Materials, 5 (2021) 113606.
[2] Shihao Zhang, …, and Shigenobu Ogata, Computational Materials Science, 235 (2024) 112843.
[3] Junping Du, …, and Shigenobu Ogata, The Journal of Chemical Physics Letters, 11 (2020) 7015.
报告人简介：
Dr. Shigenobu Ogata is a Full Professor in the Department of Mechanical Science and Bioengineering in Osaka University. He is also a Research Affiliate of the Department of Nuclear Science and Engineering, Massachusetts Institute of Technology (MIT), USA, and an editor of Progress in Materials Science (IF: 37.400).
He and his group aim to develop reliable theoretical models and neural network models for describing various nonlinear multiscale and/or multiphysics phenomena that appear in solid materials, and then to design materials with novel functions and a deformation process controlled at an atomic level in a predictive manner. He developed many mature and widely accepted models for the strength and deformation of materials; Amorphous deformation, Strength of crystal, Dislocation and Diffusion driven deformation, Hydrogen embrittlement and so on. He has published over 200 papers in Science, Advanced Materials, Nat. Commun., Nano Letters, etc. that received 8900+ citations and 42 h-index (4550+ citations and 34 h-index since 2019). His has received more than academic 20 awards.