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Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis
Author(s) -
Alex Belianinov,
Panchapakesan Ganesh,
Wenzhi Lin,
B. C. Sales,
Athena S. Sefat,
Stephen Jesse,
Minghu Pan,
Sergei V. Kalinin
Publication year - 2014
Publication title -
apl materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.571
H-Index - 60
ISSN - 2166-532X
DOI - 10.1063/1.4902996
Subject(s) - electronic structure , materials science , scanning tunneling microscope , chalcogen , multivariate statistics , local density of states , spectroscopy , chemical physics , condensed matter physics , nanotechnology , crystallography , chemistry , physics , computer science , machine learning , quantum mechanics
Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1−xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces

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