Image-based Characterization, Stochastic Reconstruction, and Modeling of Li-ion Battery Electrode Microstructures

A li-ion battery microstructure-resolved characterization, reconstruction, and simulation workflow is developed to study microstructure mechanical and transport properties. First, a microscopic image analysis workflow is proposed to characterize key microstructure features. Second, a stochastic reconstruction method is proposed to generate statistically equivalent 3D microstructure model based on the statistical functions obtained by image characterization. Third, mechanical and transport property simulation models are established to determine the microstructure properties. This workflow is first applied to examine the relationships between microstructure mechanical properties and transport properties. Next, this workflow is applied to explain the irreversible expansion of lithium-ion battery Graphite Electrodes during charge-discharge cycles. Reversible and irreversible volume changes have been observed in lithium-ion batteries. The irreversible volume changes are traditionally explained by the formation of solid electrolyte interphase (SEI) layers on the surface of electrode particles. In addition to the formation of SEI, this thesis identifies that plastic flow in the microstructure is another critical reason for the irreversible volume expansion. It is observed that the deformation and spatial rearrangement of electrode particles contribute to the irreversible volume expansion. The mass transport properties (e.g. porosity, diffusivity, and tortuosity) during the volume expansion-contraction cycles are also simulated to shed light on the impact on battery performances. The simulation results are confirmed by experimentation tests. Microscopic images of electrodes from lithium-ion battery cells with different number of charge-discharge cycles are obtained and characterized to confirm the predicted trend in microstructure evolution.