(439a) Multiscale Simulation of Cbd Formation in Battery Slurries

Over the last decade, the use of Li-ion batteries in electric vehicles has led to a rapid increase in the demand for high-capacity, high-performance batteries. A key factor influencing battery performance is the microstructure of the electrode, which is formed by mixing active material, conductive additives, and binder into a slurry. This slurry is then coated onto a metal foil, dried, and calendared to form the electrode.

The key structure in the battery electrode is Carbon Binder Domain (CBD), which is formed during the hour-long mixing process and its microstructure can be significantly impacted by mixing. The formation of CBD involves complex colloidal particle-fluid interactions such as agglomeration, breakup and polymer bridging that happen during the entire mixing process. Despite its importance, predictive models for CBD evolution are currently lacking and mixing protocols are typically developed through experience or costly trial-and-error experiments.

In this work, we develop a physics-based multiscale simulation framework to predict the CBD microstructure evolution and rheology during mixing. We begin by generating realistic carbon black aggregates using a stochastic algorithm designed to mimic the morphology of actual particles. Mesoscale simulations are then performed to resolve particle-level interactions under flow conditions, capturing the competing dynamics of agglomeration and breakup. A Fast Stokesian dynamics method is used to capture hydrodynamic interactions between aggregates accurately. The resulting statistical data from these simulations will inform continuum-scale models, including Computational Fluid Dynamics (CFD) and Population Balance Equations (PBE), enabling us to bridge particle dynamics with bulk mixing behavior. This framework can help us better understand CBD formation mechanisms and provides a strong foundation to optimize existing mixing methods and evaluate new mixing technologies.