(Invited) Understanding Macroscopic Battery Degradation Observations through Ab Initio Theory, Atomistic and Coarse-Grained Simulations, and Experiments

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In the era of vehicle electrification, automation is also an important component, and this requires simulations able to reproduce experimental observables with maximum fidelity and a minimum of experimental data. This means prediction. However, how far or how close are we from prediction? In this talk, I will focus on battery degradation phenomena, certainly associated with materials evolution, and illustrate methodologies able to generate useful predictions of dynamic changes in battery materials and components during cycling. The methods cover a wide range of scales and phenomena, from atomistic effects of electrochemical and chemical reactions to transport and phase nucleation processes. In our analysis, we find that such abundance of coexistent events goes along with environment richness: multiple dissimilar materials, and complex phases and interfaces. We will show the development of a new coarse-grained algorithm that follows the physical events receiving input from ab initio methods and providing a realistic description of plating and stripping processes coexisting with chemical, electrochemical, and nucleation reactions in complex electrolytes reducing on the Li metal surface during cycling of Li metal batteries.