Multivariate classification of echellograms: a new perspective in Laser-Induced Breakdown Spectroscopy analysis

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F01962001%3A_____%2F17%3AN0000001" target="_blank" >RIV/01962001:_____/17:N0000001 - isvavai.cz</a>
Alternative codes found
RIV/00216305:26620/17:PU123831
Result on the web
<a href="https://www.nature.com/articles/s41598-017-03426-0" target="_blank" >https://www.nature.com/articles/s41598-017-03426-0</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41598-017-03426-0" target="_blank" >10.1038/s41598-017-03426-0</a>

Result language
angličtina
Original language name
Multivariate classification of echellograms: a new perspective in Laser-Induced Breakdown Spectroscopy analysis
Original language description
In this work, we proposed a new data acquisition approach that significantly improves the repetition rates of Laser-Induced Breakdown Spectroscopy (LIBS) experiments, where high-end echelle spectrometers and intensified detectors are commonly used. The moderate repetition rates of recent LIBS systems are caused by the utilization of intensified detectors and their slow full frame (i.e. echellogram) readout speeds with consequent necessity for echellogram-to-1D spectrum conversion (intensity vs. wavelength). Therefore, we investigated a new methodology where only the most effective pixels of the echellogram were selected and directly used in the LIBS experiments. Such data processing resulted in significant variable down-selection (more than four orders of magnitude). Samples of 50 sedimentary ores samples (distributed in 13 ore types) were analyzed by LIBS system and then classified by linear and non-linear Multivariate Data Analysis algorithms. The utilization of selected pixels from an echellogram yielded increased classification accuracy compared to the utilization of common 1D spectra.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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