Deciphering Alloy Composition in Superconducting Single-Layer FeSe(1–x)S(x) on SrTiO(3)(001) Substrates by Machine Learning of STM/S Data

[Image: see text] Scanning tunneling microscopy (STM) is a powerful technique for imaging atomic structure and inferring information on local elemental composition, chemical bonding, and electronic excitations. However, a plain visual analysis of STM images can be challenging for such determination...

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Detalles Bibliográficos
Autores principales: Zou, Qiang, Oli, Basu Dev, Zhang, Huimin, Benigno, Joseph, Li, Xin, Li, Lian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176460/
https://www.ncbi.nlm.nih.gov/pubmed/37125966
http://dx.doi.org/10.1021/acsami.2c23324

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10176460/
https://www.ncbi.nlm.nih.gov/pubmed/37125966
http://dx.doi.org/10.1021/acsami.2c23324

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