Toolkit for spectral and multivariate statistical analysis of XPEEM images for studying composite energy materials

X-ray photoemission electron microscopy (XPEEM) is an advanced technique particularly well suited for elucidating the complex and buried interfacial electrochemical reactions in energy storage or conversion electrodes. Synchrotron-based (post mortem or operando) XPEEM measurements provide very high lateral spatial resolution (down to ∼50 nm) to monitor the elemental and chemical surface change upon oxidation and reduction processes. A typical XPEEM acquisition involves recording X-ray absorption images across a range of incident photon energies, generating thousands of spectra. To take full advantage of the measured datasets, an automated process for data correction and analysis for efficient interpretation is highly desirable. In this work, we provide a comprehensive toolkit consisting of a series of processing steps aiming at facilitating the analysis of complex XPEEM datasets, including (i) image drift correction and removal of non-linear distortions to align data acquired on the same region of interest across different absorption edges; (ii) local energy scale correction for energy dispersion and background subtraction for accurate spectral analysis; (iii) streamlining the analysis using threshold-based segmentation; (iv) construction of chemical maps using an unmixing algorithm, where we find that peak-ratios and peak-ratio initialised non-negative matrix factorisation (NNMF) methods achieve optimal results; (v) building a projection of the elemental and chemical maps to discriminate the various chemistries using Gaussian kernel probability density estimation and k-means clustering. We demonstrate the utility of those procedures through several examples obtained on the chemical deconvolution of the LiNi 0.6 Co 0.2 Mn 0.2 O 2 /Li 6 PS 5 Cl interphase layers in all-solid-state batteries, highlighting their capability for better data visualisation, to accelerate the analysis and to resolve complex interfacial phenomena.