Effects of Nanoparticle Geometry and Size Distribution on Diffusion Impedance of Battery Electrodes

TL;DR

This paper demonstrates that accounting for nanoparticle geometry and size distribution in impedance models enhances the accuracy of interpreting battery electrode data and enables in situ degradation detection through electrical measurements.

Contribution

It introduces improved impedance models that incorporate nanoparticle shape and size distribution, enabling more precise analysis and inverse inference of particle characteristics.

Findings

Including particle geometry improves impedance data interpretation.

Theoretical models can infer nanoparticle shape and size distribution.

Enhanced models aid in in situ battery degradation detection.

Abstract

The short diffusion lengths in insertion battery nanoparticles render the capacitive behavior of bounded diffusion, which is rarely observable with conventional larger particles, now accessible to impedance measurements. Coupled with improved geometrical characterization, this presents an opportunity to measure solid diffusion more accurately than the traditional approach of fitting Warburg circuit elements, by properly taking into account the particle geometry and size distribution. We revisit bounded diffusion impedance models and incorporate them into an overall impedance model for different electrode configurations. The theoretical models are then applied to experimental data of a silicon nanowire electrode to show the effects of including the actual nanowire geometry and radius distribution in interpreting the impedance data. From these results, we show that it is essential to account for the particle shape and size distribution to correctly interpret impedance data for battery electrodes. Conversely, it is also possible to solve the inverse problem and use the theoretical "impedance image" to infer the nanoparticle shape and/or size distribution, in some cases, more accurately than by direct image analysis. This capability could be useful, for example, in detecting battery degradation in situ by simple electrical measurements, without the need for any imaging.