The goal of this work is to develop a model to predict the microstructure of Li-ion batteries, specifically focusing on the cathode component of the batteries. This kind of model has the potential to assist researchers and battery manufacturers who are trying to optimize the capacity, cycle life, and safety of batteries. Two dynamic particle packing (DPP) microstructure models were developed in this work. The first is the DPP1 model, which simulates the final or dried electrode structure by moving spherical particles under periodic boundaries using Newton's laws of motion. The experience derived from developing DPP1 model was beneficial in making the final model, called DPP2. DPP2 is an improved version of DPP1 that includes solvent effects and is used to simulate the slurry-coating, drying, and calendering processes. Two type of properties were used to validate the DPP1 and DPP2 models in this work, although not every property was used with the DPP1 model. First are the structural properties, which include volume fraction, and electronic and ionic conductivities. Experimental structural properties were determined by analyzing 2D cross sectional images of the battery cathodes. These images were taken through focused ion beam (FIB) planarization and scanning electron microscopy (SEM). The second category are the mechanical properties, which include film elasticity and slurry viscosity. These properties were measured through experiments executed by our group. The DPP2 model was divided into two submodels : active-free and active-composite. The 2D cross sectional images of the simulated structure of the models have a similar particle arrangements as the experimental structures. The submodels show reasonable agreement with the experimental values for liquid and solid mass density, shrink ratio, and elasticity. For the viscosity, both models show shear-thinning behavior, which is a characteristic of slurries. The volume fractions of the simulated structures of the active-free and active-composite models have better agreement with the experimental values, which is also reflected in the 2D cross sectional images of the structure.
College and Department
Ira A. Fulton College of Engineering and Technology; Chemical Engineering
BYU ScholarsArchive Citation
Chao, Chien-Wei, "An Improved Dynamic Particle Packing Model for Prediction of the Microstructure in Porous Electrodes" (2015). Theses and Dissertations. 5632.
electrochemistry, structure reconstruction, FIB imaging, LJ potential, granular force