Using resistor network models to predict the transport properties of solid-state battery composites.

Solid-state batteries use composites of solid ion conductors and active materials as electrode materials. The effective transport of charge carriers and heat thereby strongly determines the overall solid-state battery performance and safety. However, the phase space for optimization of the composition of solid electrolyte, active material, additive is too large to cover experimentally. In this work, a resistor network model is presented that successfully describes the transport phenomena in solid-state battery composites, when benchmarked against experimental data of the electronic, ionic, and thermal conductivity of LiNi_0.83Co_0.11Mn_0.06O₂-Li₆PS₅Cl positive electrode composites. To highlight the broadness of the approach, literature data are examined using the proposed model. As the model is easily accessible and expandable, without the need for high computing power, it offers valuable guidance for experimentalists helping to streamline the tedious process of performing a multitude of experiments to understand and optimize the effective transport of composite electrodes. Effective conductivity is a key performance indicator for solid-state battery electrodes that is influenced by both composition and microstructure. Here, authors present a simple resistor network model to guide the development of composite electrodes towards optimized effective transport. [ABSTRACT FROM AUTHOR]