Deep learning assisted modeling of Li-ion transport in SEI: a graph neural network based study

Understanding Li-ion transport through the solid electrolyte interphase (SEI) is essential for improving the stability of lithium-metal batteries, as nonuniform ionic transport through the inorganic SEI can promote spatially localized Li deposition and dendrite formation. In this work, we develop a deep-learning-assisted framework to model Li-ion transport across the inorganic SEI by combining density functional theory (nudged elastic band) calculations with graph neural network learning. A syst