Abstract
Extended electron loss fine structure (EXELFS) compromises modulations in the high-energy segment of the core-loss fine edge of electron energy loss spectroscopy (EELS), providing valuable insights into the local atomic environment, such as inter-atomic distances, coordination numbers, bond angles and atomic disorder. Combining EXELFS with the sub nanometre spatial resolution of scanning transmission electron microscopy (STEM) enables two dimensional mapping of local structural order and coordination. Radial distribution functions (RDFs) derived from spatially resolved EXELFS spectra are clustered using unsupervised machine learning, aided with simulations, to give a quantitative measure of spatial variation in interatomic distances and coordination across thin film samples, thus enabling direct visualization and analysis of nanoscale structural heterogeneity.