The coupling between electrochemical reactions, mechanics, and phase separation in some lithium-ion battery materials indicates the need for multiphysics modeling. Yet certain material properties and constitutive laws can be difficult to disentangle and measure separately despite the availability of advanced imaging. In this talk, I will share our work using partial-differential-equation (PDE)-constrained optimization and Bayesian inference to learn the continuum models of lithium intercalation materials from microscopy images and X-ray diffraction data. We extracted thermodynamic and reaction kinetic models, spatial heterogeneity, and chemo-mechanical coupling, demonstrating the possibility of achieving full utilization of the dataset. In addition to experimental data, I will show recent work where we learned continuum models of phase separation from molecular dynamics simulation data. If time permits, I will also talk about applications of these continuum models in biological systems.
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