Cargando…
Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data
We have successfully demonstrated that although there are significant analytical challenges involved in the qualitative discrimination analysis of sub-mm sized (microfragment) glass samples, the task can be solved with very good accuracy and reliability with the multivariate chemometric evaluation o...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030928/ https://www.ncbi.nlm.nih.gov/pubmed/35459029 http://dx.doi.org/10.3390/s22083045 |
_version_ | 1784692264144994304 |
---|---|
author | Palásti, Dávid Jenő Kopniczky, Judit Vörös, Tamás Metzinger, Anikó Galbács, Gábor |
author_facet | Palásti, Dávid Jenő Kopniczky, Judit Vörös, Tamás Metzinger, Anikó Galbács, Gábor |
author_sort | Palásti, Dávid Jenő |
collection | PubMed |
description | We have successfully demonstrated that although there are significant analytical challenges involved in the qualitative discrimination analysis of sub-mm sized (microfragment) glass samples, the task can be solved with very good accuracy and reliability with the multivariate chemometric evaluation of laser-induced breakdown spectroscopy (LIBS) data or in combination with pre-screening based on refractive index (RI) data. In total, 127 glass samples of four types (fused silica, flint, borosilicate and soda–lime) were involved in the tests. Four multivariate chemometric data evaluation methods (linear discrimination analysis, quadratic discrimination analysis, classification tree and random forest) for LIBS data were evaluated with and without data compression (principal component analysis). Classification tree and random forest methods were found to give the most consistent and most accurate results, with classifications/identifications correct in 92 to 99% of the cases for soda–lime glasses. The developed methods can be used in forensic analysis. |
format | Online Article Text |
id | pubmed-9030928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90309282022-04-23 Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data Palásti, Dávid Jenő Kopniczky, Judit Vörös, Tamás Metzinger, Anikó Galbács, Gábor Sensors (Basel) Article We have successfully demonstrated that although there are significant analytical challenges involved in the qualitative discrimination analysis of sub-mm sized (microfragment) glass samples, the task can be solved with very good accuracy and reliability with the multivariate chemometric evaluation of laser-induced breakdown spectroscopy (LIBS) data or in combination with pre-screening based on refractive index (RI) data. In total, 127 glass samples of four types (fused silica, flint, borosilicate and soda–lime) were involved in the tests. Four multivariate chemometric data evaluation methods (linear discrimination analysis, quadratic discrimination analysis, classification tree and random forest) for LIBS data were evaluated with and without data compression (principal component analysis). Classification tree and random forest methods were found to give the most consistent and most accurate results, with classifications/identifications correct in 92 to 99% of the cases for soda–lime glasses. The developed methods can be used in forensic analysis. MDPI 2022-04-15 /pmc/articles/PMC9030928/ /pubmed/35459029 http://dx.doi.org/10.3390/s22083045 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Palásti, Dávid Jenő Kopniczky, Judit Vörös, Tamás Metzinger, Anikó Galbács, Gábor Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data |
title | Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data |
title_full | Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data |
title_fullStr | Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data |
title_full_unstemmed | Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data |
title_short | Qualitative Analysis of Glass Microfragments Using the Combination of Laser-Induced Breakdown Spectroscopy and Refractive Index Data |
title_sort | qualitative analysis of glass microfragments using the combination of laser-induced breakdown spectroscopy and refractive index data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9030928/ https://www.ncbi.nlm.nih.gov/pubmed/35459029 http://dx.doi.org/10.3390/s22083045 |
work_keys_str_mv | AT palastidavidjeno qualitativeanalysisofglassmicrofragmentsusingthecombinationoflaserinducedbreakdownspectroscopyandrefractiveindexdata AT kopniczkyjudit qualitativeanalysisofglassmicrofragmentsusingthecombinationoflaserinducedbreakdownspectroscopyandrefractiveindexdata AT vorostamas qualitativeanalysisofglassmicrofragmentsusingthecombinationoflaserinducedbreakdownspectroscopyandrefractiveindexdata AT metzingeraniko qualitativeanalysisofglassmicrofragmentsusingthecombinationoflaserinducedbreakdownspectroscopyandrefractiveindexdata AT galbacsgabor qualitativeanalysisofglassmicrofragmentsusingthecombinationoflaserinducedbreakdownspectroscopyandrefractiveindexdata |