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

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dc.contributor.authorPořízka, Pavelcs
dc.contributor.authorKlus, Jakubcs
dc.contributor.authorMašek, Jancs
dc.contributor.authorRajnoha, Martincs
dc.contributor.authorProchazka, Davidcs
dc.contributor.authorModlitbová, Pavlínacs
dc.contributor.authorNovotný, Jancs
dc.contributor.authorBurget, Radimcs
dc.contributor.authorNovotný, Karelcs
dc.contributor.authorKaiser, Jozefcs
dc.coverage.issue3160cs
dc.coverage.volume7cs
dc.date.accessioned2020-08-04T10:59:53Z
dc.date.available2020-08-04T10:59:53Z
dc.date.issued2017-12-01cs
dc.description.abstractIn 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.en
dc.formattextcs
dc.format.extent1-12cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationScientific Reports. 2017, vol. 7, issue 3160, p. 1-12.en
dc.identifier.doi10.1038/s41598-017-03426-0cs
dc.identifier.issn2045-2322cs
dc.identifier.other136910cs
dc.identifier.urihttp://hdl.handle.net/11012/69360
dc.language.isoencs
dc.publisherSpringer Naturecs
dc.relation.ispartofScientific Reportscs
dc.relation.urihttps://www.nature.com/articles/s41598-017-03426-0cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/2045-2322/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectAnalytical chemistryen
dc.subjectGeologyen
dc.subjectStatisticsen
dc.titleMultivariate classification of echellograms: a new perspective in Laser-Induced Breakdown Spectroscopy analysisen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-136910en
sync.item.dbtypeVAVen
sync.item.insts2020.09.02 13:55:01en
sync.item.modts2020.09.02 13:39:31en
thesis.grantorVysoké učení technické v Brně. Středoevropský technologický institut VUT. Charakterizace materiálů a pokročilé povlaky 1-06cs
thesis.grantorVysoké učení technické v Brně. . AtomTrace s.r.o.cs
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inženýrství. Ústav fyzikálního inženýrstvícs
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Centrum senzorických, informačních a komunikačních systémůcs
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
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Centrum senzorických, informačních a komunikačních systémů
Charakterizace materiálů a pokročilé povlaky 1-06
Ústav fyzikálního inženýrství
Ústav telekomunikací