X-ray hyperspectral classification of the metal-insulator transition in NdNiO3

Rare-earth nickelates, such as NdNiO3, belong to a family of strongly correlated electron systems in which the electronic and magnetic properties are strongly coupled: NdNiO3 undergoes a temperature driven first-order Metal to Insulator phase transition (MIT) accompanied by charge-order and spin density wave-order phase transition. During the phase transition, the underlying evolution of the insulating domains are averaged out by the limited spatial resolution of conventional bulk probes but, soft X-ray photoemission electron microscopy (X-PEEM) can be applied in order to elucidate nanoscale heterogeneity. In this work we apply X-PEEM to image cooling and heating MITs and develop machine learning based analysis techniques, mainly Principle Component Analysis (PCA) and Independent Component Analysis (ICA) with k-means classification, to classify thermally evolving metallic and insulating domains. The performance of our suite of classifiers is evaluated in this novel application and we discuss their physical interpretation on the basis of charge ordering through the MIT. This class of tools can be applied to other experimental hyperspectral data to extract the characteristics of coexisting phases from otherwise intractably large datasets.