Professor Bai's lab is Inventing new analytical tools, both experimental and mathematical, to investigate the fundamental science in advanced electrochemical energy systems. His research focuses on the development of next-generation batteries. The Battery Analytical Investigation (BAI) Group he leads adopts a combined theoretical and experimental approach to: (i) probe the in situ electrochemical dynamics of miniature electrodes down to nanoscales; (ii) capture the heterogeneous and stochastic nature of advanced electrodes to understand and optimize the macroscopic behavior; and (iii) identify the theoretical pathways and boundaries for the rational design of materials, electrodes and batteries through physics-based mathematical modeling and simulation. Knowledge and tools developed in the BAI Group also apply to and benefit the design of other electrochemical energy systems like supercapacitors and fuel cells. Jointly trained at MIT and Tsinghua University, Professor Bai obtained his PhD degree in Mechanical Engineering from Tsinghua University in 2012. He continued his research in the Department of Chemical Engineering at MIT as a postdoctoral associate, then senior postdoctoral associate and research scientist, prior to joining Washington University in St. Louis as a tenure-track Assistant Professor in 2017. With his expertise in physics-based mathematical modeling and analytical electrochemistry, Professor Bai has published original research in scientific journals including Science, Nature Communications, Energy & Environmental Science, Nano Letters, etc. His unique contributions earned him the Oronzio and Niccolò De Nora Foundation Young Author Prize from the International Society of Electrochemistry (ISE) in 2014, and the ISE Prize for Electrochemical Materials Science in 2018.
“Our unique transparent cell revealed that the voltage of battery could look quite normal, even though the separator has been penetrated by a lithium metal filament. Without seeing what is happening inside, you could be easily fooled by the seemingly reas
“We found a way — not just to do it ‘more accurately,’ but now we can make predictions because we know the true physics of the system." Professor Peng Bai on his lab's novel approach to predicting if a battery will fail.