Understanding the effect of particle size and size standard deviation on lithium-ion concentration and discharge behavior of heterogeneous electrode

Abstract

With the growing demand for electric vehicles and renewable energy storage, enhancing battery energy density has become a focal point of current research. Increasing electrode thickness is an effective strategy, but it is accompanied by the complexification of the microstructure, leading to reduced lithium-ion transport efficiency. In particular, the particle size and size standard deviation of active materials significantly influence the electrode microstructure. This study developed a new MATLAB algorithm to construct a heterogeneous particle packing cell model, using particle radius and size standard deviation as key parameters. The effects of particle size and size spatial distribution on battery performance were investigated by analyzing the Li-ion concentration distribution and the depth of discharge. The results showed that the short diffusion paths of small particles facilitated more effective lithiation. Random mixing of large and small particles significantly enhanced lithium-ion transport compared to large particles alone. Furthermore, the standard deviation of particle size had a notable impact on battery performance, and electrodes with different particle radii exhibited different sensitivities to this standard deviation. An optimal particle size standard deviation was identified that could enhance lithium-ion diffusion and improve rate performance. Additionally, the spatial distribution of particle sizes along the electrode thickness also affected lithium-ion transport behavior. The lithium-ion transport results under these different particle distributions provide valuable insights for the design of electrode microstructures, potentially advancing battery technology.