1. An automatic method for atom identification in scanning tunnelling microscopy images of Fe-chalcogenide superconductors
- Author
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Annalisa Perasso, Emilio Bellingeri, Michele Piana, S. Kawale, Carlo Ferdeghini, Cristian Toraci, Renato Buzio, A. Gerbi, and Anna Maria Massone
- Subjects
Histology ,Fuzzy clustering ,business.industry ,Chalcogenide ,Computer science ,Nanotechnology ,Image processing ,Pathology and Forensic Medicine ,Condensed Matter::Materials Science ,chemistry.chemical_compound ,ComputingMethodologies_PATTERNRECOGNITION ,chemistry ,Atom ,Microscopy ,Optoelectronics ,Thin film ,business ,Nanoscopic scale ,Quantum tunnelling - Abstract
We describe a computational approach for the automatic recognition and classification of atomic species in scanning tunnelling microscopy images. The approach is based on a pipeline of image processing methods in which the classification step is performed by means of a Fuzzy Clustering algorithm. As a representative example, we use the computational tool to characterize the nanoscale phase separation in thin films of the Fe-chalcogenide superconductor FeSex Te1-x , starting from synthetic data sets and experimental topographies. We quantify the stoichiometry fluctuations on length scales from tens to a few nanometres.
- Published
- 2015