Analysis of Minerals Using Handheld Laser-Induced Breakdown Spectroscopy Technology

被引:1
作者
Mezoued, Naila [1 ]
Fabre, Cecile [1 ]
Cauzid, Jean [1 ]
Kim, Yonghwi [1 ]
Jatteau, Marjolene [1 ]
机构
[1] Univ Lorraine, Fac Sci & Technol, CNRS, GeoRessources, F-54506 Vandoeuvre Les Nancy, France
基金
欧盟地平线“2020”;
关键词
laser-induced breakdown spectroscopy; handheld LIBS; minerals; spectra; database; LIBS; IDENTIFICATION; CLASSIFICATION; ARGON; TIME;
D O I
10.3390/data10030040
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Laser-induced breakdown spectroscopy (LIBS), a rapid and versatile analytical technique, is becoming increasingly widespread within the geoscience community. Suitable for fieldwork analyses using handheld analyzers, the elemental composition of a sample is revealed by generating plasma using a high-energy laser, providing a practical solution to numerous geological challenges, including identifying and discriminating between different mineral phases. This data paper presents over 12,000 reference mineral spectra acquired using a handheld LIBS analyzer ((c) SciAps), including those of silicates (e.g., beryl, quartz, micas, spodumene, vesuvianite, etc.), carbonates (e.g., dolomite, magnesite, aragonite), phosphates (e.g., amblygonite, apatite, topaz), oxides (e.g., hematite, magnetite, rutile, chromite, wolframite), sulfates (e.g., baryte, gypsum), sulfides (e.g., chalcopyrite, pyrite, pyrrhotite), halides (e.g., fluorite), and native elements (e.g., sulfur and copper). The datasets were collected from 170 pure mineral samples in the form of crystals, powders, and rock specimens, during three research projects: NEXT, Labex Ressources 21, and ARTeMIS. The extensive spectral range covered by the analyzer spectrometers (190-950 nm) allowed for the detection of both major (>1 wt.%) and trace (<1 wt.%) elements, recording a unique spectral signature for each mineral. Mineral spectra can serve as reference data to (i) identify relevant emission lines and spectral ranges for specific minerals, (ii) be compared to unknown LIBS spectra for mineral identification, or (iii) constitute input data for machine learning algorithms. Dataset: https://doi.org/10.24396/ORDAR-165. Dataset License: CC-BY-NC-SA
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页数:10
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共 41 条
[1]   Spatial characterization of laser induced plasmas obtained in air and argon with different laser focusing distances [J].
Aguilera, JA ;
Bengoechea, J ;
Aragón, C .
SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2004, 59 (04) :461-469
[2]   Quantitative Classification of Quartz by Laser Induced Breakdown Spectroscopy in Conjunction with Discriminant Function Analysis [J].
Ali, A. ;
Khan, M. Z. ;
Rehan, I. ;
Rehan, K. ;
Muhammad, R. .
JOURNAL OF SPECTROSCOPY, 2016, 2016
[3]   Ultrafast μLIBS imaging for the multiscale mineralogical characterization of pegmatite rocks [J].
Alvarez-Llamas, Cesar ;
Tercier, Adrian ;
Ballouard, Christophe ;
Fabre, Cecile ;
Hermelin, Sylvain ;
Margueritat, Jeremie ;
Duponchel, Ludovic ;
Dujardin, Christophe ;
Motto-Ros, Vincent .
JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY, 2024, 39 (04) :1077-1086
[4]   A critical review of recent trends in sample classification using Laser-Induced Breakdown Spectroscopy (LIBS) [J].
Brunnbauer, L. ;
Gajarska, Z. ;
Lohninger, H. ;
Limbeck, A. .
TRAC-TRENDS IN ANALYTICAL CHEMISTRY, 2023, 159
[5]   Robust and interpretable mineral identification using laser-induced breakdown spectroscopy mapping [J].
Capela, Diana ;
Ferreira, Miguel F. S. ;
Lima, Alexandre ;
Dias, Filipa ;
Guimara, Diana ;
Jorge, Pedro A. S. ;
Silva, Nuno A. .
SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2023, 206
[6]   SuperCam calibration targets on board the perseverance rover: Fabrication and quantitative characterization [J].
Cousin, A. ;
Sautter, V ;
Fabre, C. ;
Dromart, G. ;
Montagnac, G. ;
Drouet, C. ;
Meslin, P. Y. ;
Gasnault, O. ;
Beyssac, O. ;
Bernard, S. ;
Cloutis, E. ;
Forni, O. ;
Beck, P. ;
Fouchet, T. ;
Johnson, J. R. ;
Lasue, J. ;
Ollila, A. M. ;
De Parseval, P. ;
Gouy, S. ;
Caron, B. ;
Madariaga, J. M. ;
Arana, G. ;
Madsen, M. Bo ;
Laserna, J. ;
Moros, J. ;
Manrique, J. A. ;
Lopez-Reyes, G. ;
Rull, F. ;
Maurice, S. ;
Wiens, R. C. .
SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2022, 188
[7]   Analysis of Garnet by Laser-Induced Breakdown Spectroscopy-Two Practical Applications [J].
Defnet, Peter A. ;
Wise, Michael A. ;
Harmon, Russell S. ;
Hark, Richard R. ;
Hilferding, Keith .
MINERALS, 2021, 11 (07)
[8]   A multivariate statistical approach for mineral geographic provenance determination using laser-induced breakdown spectroscopy and electron microprobe chemical data: A case study of copper-bearing tourmalines [J].
Dutrow, Barbara L. ;
McMillan, Nancy J. ;
Henry, Darrell J. .
AMERICAN MINERALOGIST, 2024, 109 (06) :1085-1095
[9]   Multiphase mineral identification and quantification by laser-induced breakdown spectroscopy [J].
El Haddad, Josette ;
de Lima Filho, Elton Soares ;
Vanier, Francis ;
Harhira, Aissa ;
Padioleau, Christian ;
Sabsabi, Mohamad ;
Wilkie, Greg ;
Blouin, Main .
MINERALS ENGINEERING, 2019, 134 :281-290
[10]   Classification of sedimentary and igneous rocks by laser induced breakdown spectroscopy and nanoparticle-enhanced laser induced breakdown spectroscopy combined with principal component analysis and graph theory [J].
El-Saeid, R. H. ;
Abdel-Salam, Z. ;
Pagnotta, S. ;
Palleschi, V ;
Harith, M. A. .
SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY, 2019, 158