Multivariate mapping analysis of electronic structure on atomic level

Abstract

Spatial variability of electronic structure of Fe-based superconductor FeTe0.55Se0.45 is explored on the atomic level using continuous imaging tunneling spectroscopy (CITS). Multivariate statistical analysis of the data clearly differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms. The subsequent clustering analysis allows spatial localization of region with dissimilar electronic functionality to be localized. Similar statistical analysis of calculated DOS, further confirms that chalcogens can be identified by their electronic signature and further differentiated by their local crystallographic environment.