Martin Bazant
Learning Battery Physics from Images
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Martin Z Bazant, Ph.D.
E. G. Roos (1944) Professor, Massachusetts Institute of Technology
Chemical Engineering and Mathematics
Bazant Research Group
Abstract: Learning Battery Physics from Images
Traditional methods of scientific inquiry and engineering design begin with human intelligence: Mathematical models encoding physical hypotheses are proposed, tested against experimental data and refined by fitting adjustable parameters. Recent advances in artificial intelligence appear to challenge this paradigm, since predictions can be made directly from data without the need for models, but such knowledge is often not transferrable to new situations. This talk will present a hybrid approach of solving PDE-constrained inverse problems to derive realistic models of electrochemical thermodynamics and reaction kinetics, in the context of Li-ion batteries. Examples of learning physics from image data include inferring electro-autocatalytic reaction models from x-ray diffraction spectra for metal-oxide cathodes, optical videos of lithium metal growth on graphite anodes, and x-ray adsorption imaging of driven phase separation in iron phosphate nanoparticles, including the detection of nanoscale spatial heterogeneity correlated with carbon coating thickness. Related examples for spectroscopic “images” include inversion of electrochemical impedance spectra to determine microstructural heterogeneity and of acoustic emission spectra to reveal degradation processes during battery forming.
Biography
Martin Z. Bazant is the E. G. Roos (1944) Professor of Chemical Engineering and Mathematics at the Massachusetts Institute of Technology. After a PhD in Physics at Harvard (1997), he joined the MIT faculty in Mathematics (1998) and then in Chemical Engineering (2008). He is a Fellow of the American Physical Society (Division of Fluid Dynamics), the International Society of Electrochemistry, and the Royal Society of Chemistry, and winner of the 2015 Kuznetsov Prize in Theoretical Electrochemistry (ISE), the 2018 Andreas Acrivos Award for Professional Progress in Chemical Engineering (AIChE), the 2019 MITx/edX Prize for Teaching and Learning in Massive Open Online Courses. He also serves as the Chief Scientific Advisor for Saint Gobain Ceramics and Plastics, North America.
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