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Local coexistence of VO(2) phases revealed by deep data analysis

We report a synergistic approach of micro-Raman spectroscopic mapping and deep data analysis to study the distribution of crystallographic phases and ferroelastic domains in a defected Al-doped VO(2) microcrystal. Bayesian linear unmixing revealed an uneven distribution of the T phase, which is stab...

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Detalles Bibliográficos
Autores principales: Strelcov, Evgheni, Ievlev, Anton, Belianinov, Alex, Tselev, Alexander, Kolmakov, Andrei, Kalinin, Sergei V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935893/
https://www.ncbi.nlm.nih.gov/pubmed/27384473
http://dx.doi.org/10.1038/srep29216
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author Strelcov, Evgheni
Ievlev, Anton
Belianinov, Alex
Tselev, Alexander
Kolmakov, Andrei
Kalinin, Sergei V.
author_facet Strelcov, Evgheni
Ievlev, Anton
Belianinov, Alex
Tselev, Alexander
Kolmakov, Andrei
Kalinin, Sergei V.
author_sort Strelcov, Evgheni
collection PubMed
description We report a synergistic approach of micro-Raman spectroscopic mapping and deep data analysis to study the distribution of crystallographic phases and ferroelastic domains in a defected Al-doped VO(2) microcrystal. Bayesian linear unmixing revealed an uneven distribution of the T phase, which is stabilized by the surface defects and uneven local doping that went undetectable by other classical analysis techniques such as PCA and SIMPLISMA. This work demonstrates the impact of information recovery via statistical analysis and full mapping in spectroscopic studies of vanadium dioxide systems, which is commonly substituted by averaging or single point-probing approaches, both of which suffer from information misinterpretation due to low resolving power.
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spelling pubmed-49358932016-07-08 Local coexistence of VO(2) phases revealed by deep data analysis Strelcov, Evgheni Ievlev, Anton Belianinov, Alex Tselev, Alexander Kolmakov, Andrei Kalinin, Sergei V. Sci Rep Article We report a synergistic approach of micro-Raman spectroscopic mapping and deep data analysis to study the distribution of crystallographic phases and ferroelastic domains in a defected Al-doped VO(2) microcrystal. Bayesian linear unmixing revealed an uneven distribution of the T phase, which is stabilized by the surface defects and uneven local doping that went undetectable by other classical analysis techniques such as PCA and SIMPLISMA. This work demonstrates the impact of information recovery via statistical analysis and full mapping in spectroscopic studies of vanadium dioxide systems, which is commonly substituted by averaging or single point-probing approaches, both of which suffer from information misinterpretation due to low resolving power. Nature Publishing Group 2016-07-07 /pmc/articles/PMC4935893/ /pubmed/27384473 http://dx.doi.org/10.1038/srep29216 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Strelcov, Evgheni
Ievlev, Anton
Belianinov, Alex
Tselev, Alexander
Kolmakov, Andrei
Kalinin, Sergei V.
Local coexistence of VO(2) phases revealed by deep data analysis
title Local coexistence of VO(2) phases revealed by deep data analysis
title_full Local coexistence of VO(2) phases revealed by deep data analysis
title_fullStr Local coexistence of VO(2) phases revealed by deep data analysis
title_full_unstemmed Local coexistence of VO(2) phases revealed by deep data analysis
title_short Local coexistence of VO(2) phases revealed by deep data analysis
title_sort local coexistence of vo(2) phases revealed by deep data analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935893/
https://www.ncbi.nlm.nih.gov/pubmed/27384473
http://dx.doi.org/10.1038/srep29216
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