Using Physics Based Models to Predict the Conductivity of Solid Polymer Electrolytes

This study explores the conductivity of solid polymer electrolytes (SPEs) crucial for Li-ion battery technology using computational modeling. A one-dimensional case is used on a simple electrolyte domain, writing a mass balance on each species. The individual equations for each species within the model integrate both diffusion and migration terms but are mathematically altered to obtain a singular simple diffusion equation, which becomes essential for the conductivity predictions using the Nernst-Einstein equation. The electric potential then results in an analytical solution and the domain is induced under a 1 mA cm-1 alternating current. The model is then optimized with diffusion coefficients and a rate constant being independent variables and validated against electric potential experimental data from literature concerning liquid electrolytes using a Li | Li cell. This is later generalized to SPEs with the addition of a volume fraction. Employing COMSOL Multiphysics, simulations indicate that the conductivity of a 1M LiPF6 50% SPE approximates 5.3 mS cm-1, closely aligning with other experimental measurements, with the optimized parameters reflecting similar magnitudes to experimental literature as well. Future work would be to include the SPE’s ion hopping, adding to the conductivity, and continuous experimental validation. This computational approach underscores its pivotal role in advancing battery technology by enabling predictions and validation of SPE conductivities before construction. Such validation against liquid electrolyte benchmarks provides confidence in the model's ability to predict behaviors in solid electrolytes more accurately.