Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data
Abstract
Time of flight secondary ion mass spectrometry (ToF SIMS) is one of the most powerful characterization tools allowing imaging of the chemical properties of various systems and materials. It allows precise studies of the chemical composition with sub-100-nm lateral and nanometer depth spatial resolution. However, comprehensive interpretation of ToF SIMS results is challengeable, because of the data volume and its multidimensionality. Furthermore, investigation of the samples with pronounced topographical features are complicated by the spectral shift. In this work we developed approach for the comprehensive ToF SIMS data interpretation based on the data analytics and automated extraction of the sample topography based on time of flight shift. We further applied this approach to investigate correlation between biological function and chemical composition in Arabidopsis roots.
- Authors:
-
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Tennessee, Knoxville, TN (United States)
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1412060
- Grant/Contract Number:
- AC05-00OR22725
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Scientific Reports
- Additional Journal Information:
- Journal Volume: 7; Journal Issue: 1; Journal ID: ISSN 2045-2322
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
Citation Formats
Ievlev, Anton V., Belianinov, Alexei, Jesse, Stephen, Allison, David P., Doktycz, Mitchel John, Retterer, Scott T., Kalinin, Sergei V., and Ovchinnikova, Olga S. Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data. United States: N. p., 2017.
Web. doi:10.1038/s41598-017-17049-y.
Ievlev, Anton V., Belianinov, Alexei, Jesse, Stephen, Allison, David P., Doktycz, Mitchel John, Retterer, Scott T., Kalinin, Sergei V., & Ovchinnikova, Olga S. Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data. United States. https://doi.org/10.1038/s41598-017-17049-y
Ievlev, Anton V., Belianinov, Alexei, Jesse, Stephen, Allison, David P., Doktycz, Mitchel John, Retterer, Scott T., Kalinin, Sergei V., and Ovchinnikova, Olga S. Wed .
"Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data". United States. https://doi.org/10.1038/s41598-017-17049-y. https://www.osti.gov/servlets/purl/1412060.
@article{osti_1412060,
title = {Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data},
author = {Ievlev, Anton V. and Belianinov, Alexei and Jesse, Stephen and Allison, David P. and Doktycz, Mitchel John and Retterer, Scott T. and Kalinin, Sergei V. and Ovchinnikova, Olga S.},
abstractNote = {Time of flight secondary ion mass spectrometry (ToF SIMS) is one of the most powerful characterization tools allowing imaging of the chemical properties of various systems and materials. It allows precise studies of the chemical composition with sub-100-nm lateral and nanometer depth spatial resolution. However, comprehensive interpretation of ToF SIMS results is challengeable, because of the data volume and its multidimensionality. Furthermore, investigation of the samples with pronounced topographical features are complicated by the spectral shift. In this work we developed approach for the comprehensive ToF SIMS data interpretation based on the data analytics and automated extraction of the sample topography based on time of flight shift. We further applied this approach to investigate correlation between biological function and chemical composition in Arabidopsis roots.},
doi = {10.1038/s41598-017-17049-y},
journal = {Scientific Reports},
number = 1,
volume = 7,
place = {United States},
year = {Wed Dec 06 00:00:00 EST 2017},
month = {Wed Dec 06 00:00:00 EST 2017}
}
Web of Science
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