Non-Negative Matrix Factorization for 2D-XAS Images of Lithium Ion Batteries

TL;DR

This paper introduces a non-negative matrix factorization method to analyze 2D-XAS images of lithium-ion batteries, enabling detection of chemical non-uniformities and changes in the state of charge.

Contribution

The proposed method effectively decomposes 2D-XAS data into spatial domains and spectra, revealing subtle spectral changes related to battery charge states.

Findings

Detected transition-energy shifts indicating charge state changes

Identified spectral variations due to orbital hybridization

Decomposed complex spectral data into meaningful spatial and spectral components

Abstract

Lithium-ion secondary batteries have been used in a wide variety of purposes, such as for powering mobile devices and electric vehicles, but their performance should be improved. One of the factors that limits their performance is the non-uniformity of the chemical reaction in the process of charging and discharging. Many attempts have been made to elucidate the mechanism behind this reaction non-uniformity. In this paper, to detect non-uniformity in various physical properties from Co K-edge two-dimensional X-ray absorption spectroscopy (2D-XAS) images of lithium ion batteries, we propose a method that consists of one-sided orthogonal non-negative matrix factorization in combination with removal of the reference signal. The difference between X-ray absorption spectra acquired at different positions in the battery is very small. However, even in such a situation, our method can decompose the 2D-XAS data into different spatial domains and their corresponding absorption spectra. From the spectral decomposition of the obtained absorption spectra, we confirmed a transition-energy shift of the main peak as evidence for a change in the state of charge and also found spectral changes due to orbital hybridization in the decomposed spectral components.