Applications of Multiscale Simulations to Battery Material Modelling

Abstract

This thesis presents a multiscale computational framework for modeling lithium-ion battery electrodes, focusing on the interplay between microscopic particle interactions and macroscopic manufacturing processes. By integrating coarse-grained molecular dynamics, granular contact models, and image-based analysis, the work captures how particle-level phenomena drive electrode structure and performance. Active material (AM) and carbon-binder domain (CBD) particles are represented via coarse-grained beads, with parameters derived from tomographic and experimental data. Molecular dynamics simulations then replicate the electrode fabrication steps, including slurry formation, solvent drying, and calendering, the latter modeled through granularity-based contact mechanics and deformable walls. A suite of newly developed scripts translates the evolving three-dimensional particle arrangements into voxel-based images for quantitative porosity and homogeneity assessments. Results reveal that processing conditions- particularly wall speeds, damping coefficients, LJ Forcefield parameters, diameter and pressure corrections, and elastic moduli strongly influence final porosity and mechanical integrity, highlighting the need for careful parameter tuning. Additionally, discrepancies between theoretical pressure targets and simulated values underscore the complexity of reliably modeling contact forces and dissipative effects at mesoscopic scales. The thesis demonstrates that when carefully parameterized, coarse-grained Force fields and contact models can reproduce experimentally observed electrode properties and microstructures. Beyond lithium-ion systems, the techniques developed herein offer broader applications to other energy-storage technologies that rely on complex particle assemblies. Overall, this work advances predictive multiscale modeling of battery electrodes by bridging fundamental physical insight with practical engineering constraints, ultimately informing design decisions for next-generation, high-performance energy storage devices.