Data driven approach to reconstruct and interpret ELNES spectra

Abstract

ELNES is the powerful method with high temporal and spatial resolution to analyze local atomic and electron structures. However, extracting that information from the experimental spectra requires some difficulties. It requires the theoretical calculations and expert knowledge and cannot deal with big data. Here, we developed the new approach to reconstruct and interpret ELNES spectra. Our method is based on hierarchical clustering and decision tree method, and enable to tie the structure information with the spectrum shape. Moreover, it is noted that our method is not applicable only to spectrum data, for instance, XAS and DOS, but also image data in principle.