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Image-Based Chemical Structure Determination
Chemical imaging is a powerful tool for understanding the chemical composition and nature of heterogeneous samples. Recent developments in elemental, vibrational, and mass-spectrometric chemical imaging with high spatial resolution (50–200 nm) and reasonable timescale (a few hours) are capable of pr...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5533744/ https://www.ncbi.nlm.nih.gov/pubmed/28754996 http://dx.doi.org/10.1038/s41598-017-07041-x |
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author | Ofner, Johannes Brenner, Florian Wieland, Karin Eitenberger, Elisabeth Kirschner, Johannes Eisenmenger-Sittner, Christoph Török, Szilvia Döme, Balazs Konegger, Thomas Kasper-Giebl, Anne Hutter, Herbert Friedbacher, Gernot Lendl, Bernhard Lohninger, Hans |
author_facet | Ofner, Johannes Brenner, Florian Wieland, Karin Eitenberger, Elisabeth Kirschner, Johannes Eisenmenger-Sittner, Christoph Török, Szilvia Döme, Balazs Konegger, Thomas Kasper-Giebl, Anne Hutter, Herbert Friedbacher, Gernot Lendl, Bernhard Lohninger, Hans |
author_sort | Ofner, Johannes |
collection | PubMed |
description | Chemical imaging is a powerful tool for understanding the chemical composition and nature of heterogeneous samples. Recent developments in elemental, vibrational, and mass-spectrometric chemical imaging with high spatial resolution (50–200 nm) and reasonable timescale (a few hours) are capable of providing complementary chemical information about various samples. However, a single technique is insufficient to provide a comprehensive understanding of chemically complex materials. For bulk samples, the combination of different analytical methods and the application of statistical methods for extracting correlated information across different techniques is a well-established and powerful concept. However, combined multivariate analytics of chemical images obtained via different imaging techniques is still in its infancy, hampered by a lack of analytical methodologies for data fusion and analysis. This study demonstrates the application of multivariate statistics to chemical images taken from the same sample via various methods to assist in chemical structure determination. |
format | Online Article Text |
id | pubmed-5533744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-55337442017-08-03 Image-Based Chemical Structure Determination Ofner, Johannes Brenner, Florian Wieland, Karin Eitenberger, Elisabeth Kirschner, Johannes Eisenmenger-Sittner, Christoph Török, Szilvia Döme, Balazs Konegger, Thomas Kasper-Giebl, Anne Hutter, Herbert Friedbacher, Gernot Lendl, Bernhard Lohninger, Hans Sci Rep Article Chemical imaging is a powerful tool for understanding the chemical composition and nature of heterogeneous samples. Recent developments in elemental, vibrational, and mass-spectrometric chemical imaging with high spatial resolution (50–200 nm) and reasonable timescale (a few hours) are capable of providing complementary chemical information about various samples. However, a single technique is insufficient to provide a comprehensive understanding of chemically complex materials. For bulk samples, the combination of different analytical methods and the application of statistical methods for extracting correlated information across different techniques is a well-established and powerful concept. However, combined multivariate analytics of chemical images obtained via different imaging techniques is still in its infancy, hampered by a lack of analytical methodologies for data fusion and analysis. This study demonstrates the application of multivariate statistics to chemical images taken from the same sample via various methods to assist in chemical structure determination. Nature Publishing Group UK 2017-07-28 /pmc/articles/PMC5533744/ /pubmed/28754996 http://dx.doi.org/10.1038/s41598-017-07041-x Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Ofner, Johannes Brenner, Florian Wieland, Karin Eitenberger, Elisabeth Kirschner, Johannes Eisenmenger-Sittner, Christoph Török, Szilvia Döme, Balazs Konegger, Thomas Kasper-Giebl, Anne Hutter, Herbert Friedbacher, Gernot Lendl, Bernhard Lohninger, Hans Image-Based Chemical Structure Determination |
title | Image-Based Chemical Structure Determination |
title_full | Image-Based Chemical Structure Determination |
title_fullStr | Image-Based Chemical Structure Determination |
title_full_unstemmed | Image-Based Chemical Structure Determination |
title_short | Image-Based Chemical Structure Determination |
title_sort | image-based chemical structure determination |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5533744/ https://www.ncbi.nlm.nih.gov/pubmed/28754996 http://dx.doi.org/10.1038/s41598-017-07041-x |
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