Accelerated Computational Materials Design for Next­ Generation Batteries

Yifei Mo
Department of Materials Science and Engineering, University of Maryland, College Park, MD, USA 

EXTENDED ABSTRACT: The development of next-generation new technology is often hinged on the limited performance of critical materials. As a notable example, the development of solid-state batteries is limited by the shortcomings of multiple properties of solid electrolyte, electrode, and materials interfaces. In this presentation, we will discuss the advancements in various computation techniques encompassing first principles computation, large materials database, and machine learning, motivated by Materials Genome Engineering, leading to the accelerated computation design of new materials with enhanced performances. Many materials discovered by computation have been experimentally verified. The computation framework combining a set of techniques represents a new MGE paradigm for materials design and discovery for accelerated enabling next-generation technologies.
Keywords: Computational materials design; solid-state battery; solid electrolyte 

Brief Introduction of Speaker
Prof. Yifei Mo

Prof. Yifei Mo is a Professor of Materials Science and Engineering at the University of Maryland, College Park, USA. Dr. Mo's research aims to advance the understanding, design, and discovery of engineering materials through cutting-edge computational techniques. His research has been published in leading peer-reviewed journals including Nature, Science, Nature Materials, Nature Communications, Science Advances, Joule, Journal of the American Chemical Society, Advanced Materials, Angewandte Chemie, and has been a Clarivate Highly Cited Researcher. He has been serving as an editorial board member of Energy Storage Materials, NPJ Computational Materials, Advanced Theory and Simulations, Journal of Materials Informatics (Youth member), and Energy Materials.