Application of Computational Materials Science in Li/Na-ion Battery Materials Research and Development
Abstract:Lithium/Sodium-ion batteries can offer a possible near-term solution for environment-friendly transportation and energy storage for renewable energies sources, such as solar and wind. In this talk, I will present an introduction to the combined application of first principles methods based on density functional theory (DFT), statistic mechanics, experiment and machine learning, etc, followed by an overview of the computation work aimed at designing better electrode materials. Specifically, we show how each relevant property is related to the structural component in the material that is computable, and we benchmark the computation results with experimental observations. Finally, we present some of the key challenges faced by researchers in the field.
Biography: Siqi Shi obtained his B.S. from Jiangxi Normal University in 1998. He finished his Ph.D. from Institute of Physics, Chinese Academy of Sciences, in 2004. After that, he joined the National Institute of Advanced Industrial Science and Technology of Japan and Brown University in the USA as a senior research associate, where he remained until joining Shanghai University as a professor in early 2013. He was supported by the National Excellent Youth Natural Science Foundation of China in 2016. He has published over 100 peer-review papers in international journals including Nature Communications, Journal of the American Chemical Society, and Physical Review B. These papers have earned a total citation of ~2700 and H-index of 27. His research interests are focused on the fundamentals and microscopic design of electrochemical energy storage and conversion materials, materials Informatics and data mining.