Image-Based Chemical Structure Determination

Johannes Ofner, Florian Brenner, Karin Wieland, Elisabeth Eitenberger, Johannes Kirschner, Christoph Eisenmenger-Sittner, Szilvia Török, Balazs Döme, Thomas Konegger, Anne Kasper-Giebl, Herbert Hutter, Gernot Friedbacher, Bernhard Lendl, Hans Lohninger

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Abstract

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.

Original languageEnglish
Article number6832
JournalScientific reports
Volume7
Issue number1
DOIs
Publication statusPublished - Dec 1 2017

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ASJC Scopus subject areas

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Cite this

Ofner, J., Brenner, F., Wieland, K., Eitenberger, E., Kirschner, J., Eisenmenger-Sittner, C., Török, S., Döme, B., Konegger, T., Kasper-Giebl, A., Hutter, H., Friedbacher, G., Lendl, B., & Lohninger, H. (2017). Image-Based Chemical Structure Determination. Scientific reports, 7(1), [6832]. https://doi.org/10.1038/s41598-017-07041-x