Electro-Chemo-Mechanics | Batteries | Scientific Machine Learning
FA I. Safety & Health Assessment of Li-ion Batteries
Reviews:  on safety-focused modeling;  on microstructure-resolved modeling;  on battery reuse and recycling.
Experimentation:  on standardization of cell-level tests;  on micro tests of battery materials;  on plastic deformation of porous electrodes.
Computation.  on data-driven model;  on detailed finite element model;  on homogenized FEM;  on microstructural model.
Current sponsors: MIT Industrial Battery Consortium (2020-2022)
FA II. Interfacial Characterization of Solid-State Batteries
Li metal mechanics:  Sedlatschek, et al. Acta Materialia. 2021
NMC-SE interfaces:  Singh, et al. In preparation
Li-SE interfaces:  Li, et al. In preparation
Current sponsors: NASA, MIT Industrial Battery Consortium
Sponsors in the past: MIT-Indonesia Seed Fund
FA III. Scientific Machine Learning for Mechanics of Energy Storage
Physics-Informed Neural Networks (PINN):  for elastic plates
Energy-based Deep Operator Learning (DeepONet):  for phase-field theories.
Current sponsors: NASA