Model-System Diagnostics for Lithium-Metal-Based Batteries
Model-System Diagnostics for Lithium-Metal-Based Batteries
Abstract
All solid-state batteries are promising next-generation energy storage systems. In this project, we use oxidative-stable superionic halides as the model solid electrolytes to gain fundamental understanding in solid-state chemistry, interfacial reactivities, kinetic barriers, and failure mechanisms at materials level and cell level. I will discuss our strategies in developing high-voltage composite cathodes capable of stable long-term cycling, and design principles for Li alloy anodes that lead to stable interfaces between the solid electrolyte and the anode.
Speaker
Guoying ChenGuoying Chen is a Staff Scientist in the Energy Storage and Distributed Resources Division at Lawrence Berkeley National Laboratory. She holds a M.S. degree in Organic Chemistry from Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences and a Ph.D. degree in Chemistry from the Pennsylvania State University. She joined Lawrence Berkeley National Laboratory as a postdoctoral researcher in 2002. Her research involves the discovery, synthesis, and optimization of functional materials based on fundamental understanding from advanced diagnostic studies. Current projects focus on developing advanced cathode materials (Ni-rich NMCs, Li- and Mn-rich oxides and oxyfluorides), developing all solid-state batteries, and enabling extreme fast charge of lithium-ion batteries. She has authored over 100 peer-reviewed articles and she holds a number of patents on these topics. She has also been the recipient of prestigious awards including the 2020 and 2022 R&D 100 awards for energy storage systems. She currently serves on the editorial board and advisory board for Scientific Reports by Nature and Chem by CellPress.