报告题目：Membranes, superionic conductors, and nanocatalysts: From design to deep learning
报告人：Prof. De-en Jiang (Vanderbilt University)
时间：2024年11月15日 （周五）9:00
地点：九龙湖校区田家炳楼南203会议室
主持人：王金兰
报告摘要：
My group’s research focuses on computational materials chemistry and nanoscience in chemical separations, electrical energy storage, and nanocatalysis. In this talk, I will first discuss several design approaches to tune and control pore sizes at sub-angstrom level to achieve desired gas separation performances via graphene and fullerene membranes. Concepts of ion-gating and entropic selectivity will be demonstrated via molecular simulations. Next, I will introduce a new mechanism of superionic Li-ion transport in glassy halides such as LiNbxTa1-xCl6 enabled by anion vibrations and revealed by molecular dynamics simulations via machine-learning force fields of ab initio quality. In the third topic, I will show a deep-learning-in-chemistry case study where the challenge to locate the hydrides in atomically precise metal-hydride nanocluster catalysts was addressed by convolutional neural networks. In each of the studies, one will see a close interplay between computation and experiment, to understand and design functional materials.
报告人简介：
Bio: De-en Jiang is a Professor in Department of Chemical and Biomolecular Engineering and Department of Chemistry at Vanderbilt University. He received his BS and MS degrees from Peking University and PhD degree from UCLA, all in chemistry. He worked at Oak Ridge National Laboratory first as a postdoc and then as a staff scientist before joining University of California Riverside (UCR) in 2014. He was a Professor of Chemistry at UCR, as well as a cooperating faculty member of Chemical & Environmental Engineering and Materials Science and Engineering before moving to Vanderbilt in July 2022. His research focuses on computational materials and chemistry for energy and the environment. He received the DOE Early Career Award and the Presidential Early Career Awards for Scientists and Engineers. He was an elected Fellow of the American Association for the Advancement of Science. According to Google Scholar, his 390+ peer-reviewed publications have been cited over 34,000 times with an h-index of 98. He was named a Highly Cited Researcher by Clarivate in 2023.