dataset for 'Machine Learning Pipeline for the Identification and Mapping of O3 Phase along the [001] Zone Axis in Layered Ni-rich Cathodes for Li-ion Batteries'

This dataset contains scanning electron diffraction (SED) data collected from a cycled NMC811 battery cathode (LiNi₀.₈Mn₀.₁Co₀.₁O₂). A thin slice of the cathode, called a lamella, was prepared using a focused ion beam and then imaged in a transmission electron microscope (TEM). High-resolution images and diffraction patterns were recorded from each pixel in the selected area, capturing detailed structural and crystallographic information.The diffraction patterns were preprocessed using principal component analysis (PCA) and non-negative matrix factorisation (NMF) to separate meaningful signals from noise. Raw single-pixel diffraction patterns were also kept for high-resolution phase analysis.The data can be used to identify crystal phases, such as the O3 phase, which has a characteristic hexagonal diffraction pattern. Pixel-by-pixel maps were created to show the spatial distribution of different crystal phases within the particle.Overall, the dataset provides both raw and processed diffraction data that can be used for materials analysis, phase identification, and machine learning applications. It offers a detailed look at the microstructure and crystallography of battery cathode materials at the nanoscale.