December 6
@
12:00 PM
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1:00 PM
Li-ion batteries (LIBs) are widely used to power today’s portable electronics, electric vehicles (EVs), plug-in hybrid electric vehicles (PHEVs), and in utility scale battery energy storage systems (BESSs). High performance LIBs are becoming increasingly important to facilitate the ever-growing trend of electrification for achieving a low-carbon future. How to enable the design of high performance batteries over a multiscale design space that need to be optimized towards various service conditions. It is one of research topics that Dr. Li has been working on.
Dr. Li has been developing multiscale multiphysics simulations for understanding the degradation mechanisms of basic components like electrodes in LIBs and integrating physics-based simulation with machine learning for exploring novel design of electrodes. Prevalent applications of LIBs have led to a growing demand on advanced electrode materials with outperforming performances such as high energy storage capability, fast charging, and more stable cyclic performances. Extensive efforts have been devoted to searching for new active electrode materials like Tin (Sn) and silicon (Si) to purse high energy/power density. However, the electrochemical reactions of these high capacity active electrode materials during the (de)lithiation process are usually accompanied by massive volume changes which significantly mitigate mechanical integration of the battery and lead to shorten cycle life. Electrode architectures have been explored to overcome or mitigate the electrochemically induced mechanical degradation. Meanwhile, engineered electrode architecture can significantly increase the electrode/electrolyte interface where electrochemical reactions happen, and therefore enhance energy/power density. However, there are limited studies on investigating the design of architected electrodes over multiscale design space and service conditions due to lack of useful design tools. In this talk, Dr. Li will present their work on characterizing coupled multiscale failure mechanism of architected electrodes and further developing a synthetic design platform which synergizes multiscale multiphysics simulations with machine learning models for the design of high performance LIBs through architected electrodes.
Bio: Yumeng Li is an assistant professor in the department of Industrial and Enterprise Systems Engineering at University of Illinois at Urbana-Champaign. She holds a Ph.D. degree in Aerospace Engineering from Virgina Tech. Her primary research interests revolve around mechanism-driven material and structure design, computational modeling and simulation, and physics-informed machine learning. Her work includes developing multiscale /or multi-physics models for understanding cross-scale material behaviors, and physics-informed surrogate models for accelerating the design of novel material and structures towards a wide range of applications including lightweight structures, high performance energy storage, and flexible electronics. Her research has been sponsored by various agencies, such as DOE, NSF, and Naval Air Warfare Center.