Submitted by webadmin on Sun, 03/06/2022 - 22:14
Data-driven Battery Science: Elucidating The Mechanisms Of The Battery Degradation With Synchrotron X-ray Techniques
Abstract

With the growing need for sustainable energy technologies, improving the efficiency and lifetime of batteries become more and more important. It requires a better understanding of how the battery materials within the electrodes transform individually and how they interact within their own complex ecosystem and with their surrounding environment. Synchrotron X-ray techniques have demonstrated unique advantages with excellent resolution and sensitivity to structural, chemical, and morphological characteristics of the energy materials, as well as bring enormous challenges in task-specific data reduction, analysis, and interpretation. In this talk, I will present our recent efforts to accelerate the understanding of battery degradation mechanisms through jointly developing advanced multi-scale synchrotron imaging techniques and their associated data-driven approaches.

 

Speaker: Dr Jizhou LI
Date: 14 March 2022 (Monday)
Time: 10:00am – 11:00am
PosterClick here

 

Biography

Dr Jizhou LI is currently a Postdoctoral Scholar at SLAC National Accelerator Laboratory, Stanford University. He received his Ph.D. from The Chinese University of Hong Kong in 2018. With his background in mathematics and engineering, he is particularly interested in developing data-driven approaches advancing the capabilities of a broad range of imaging techniques to accelerate interdisciplinary discovery in natural science. His recent activities are focused on computational imaging and analysis in X-ray/optical microscopy and for biological/materials science.