In operando / situ X-ray diffraction experiments of Lithium-Ion batteries are often carried out on synchrotron beam lines due to the availability of high brilliance sources and the possibility to use highly penetrating high-energy radiation. We show how a state-of-the-art laboratory diffractometer with a hard-radiation silver anode and hard-radiation optimized detector is used to quickly collect high quality (Rietveld) XRPD data of Lithium-Ion batteries during several charge/discharge cycles.
Accurate phase quantities as well as crystallographic information are automatically extracted from multiple scans using complex fitting models consisting of Pawley phases to model the fixed components (Aluminum and Copper electrodes), Rietveld phases to model variable components like Li1-xCoO2, LiC6, LiC12 + Carbon and profile fit peaks to model the polymer separator. We also propose a method to model split peaks due to double pouch bag Al-foil seals and to extract useful spatial information.
Unsupervised learning (cluster analysis) is used to group and pre-sort the huge amount of raw data that is generated during these experiments. This enables us to sort all scans of one or many experiments along a virtual charge/discharge axis.