Abstract
Lithium-ion batteries, owing to their widespread application domains, are often subject to operation in extremes, e.g., fast charge and low temperatures. Porous electrodes in such systems exhibit stochasticity over hierarchy of scales. Analyzing and understanding electrode complexations across scales necessitate a data-driven framework. In this talk, we present the implications of stochastic features in electrodes, such as irregular particles, non-conformal pore network, inhomogeneity in separator microstructure and active particle aggregation. Especially, the effects of scale hierarchy are analyzed from the perspective of intercalation, thermal, and electrodeposition response under operational extremes based on a data-driven framework.
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