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

. 2017 Jun 09 ; 7 (1) : 3160. [epub] 20170609

Status PubMed-not-MEDLINE Language English Country England, Great Britain Media electronic

Document type Journal Article, Research Support, Non-U.S. Gov't

Links

PubMed 28600563
PubMed Central PMC5466686
DOI 10.1038/s41598-017-03426-0
PII: 10.1038/s41598-017-03426-0
Knihovny.cz E-resources

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.

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Miziolek, A. W., Palleschi, V. & Schechter, I. Laser Induced Breakdown Spectroscopy (Cambridge University Press, Cambridge, UK, 2006).

Noll, R. Laser-induced breakdown spectroscopy fundamentals and applications (Springer-Verlag Berlin Heidelberg, Heidelberg, Germany, 2012).

Hahn DW, Omenetto N. Laser-induced breakdown spectroscopy (libs), part i:review of basic diagnostics and plasma–particle interactions. Applied Spectroscopy. 2010;64:335–366. doi: 10.1366/000370210793561691. PubMed DOI

Hahn DW, Omenetto N. Laser-induced breakdown spectroscopy (libs), part ii:review of instrumental and methodological approaches to material analysis and applications to different fields. Applied Spectroscopy. 2012;66:347–419. doi: 10.1366/11-06574. PubMed DOI

Gottfried JL, Lucia FCD, Munson CA, Miziolek AW. Laser-induced breakdown spectroscopy for detection of explosives residues. Analytical and Bioanalytical Chemistry. 2009;395:283–300. doi: 10.1007/s00216-009-2802-0. PubMed DOI

Fortes F, Laserna J. The development of fieldable laser-induced breakdown spectrometer. Spectrochimica Acta Part B: Atomic Spectroscopy. 2010;65:975–990. doi: 10.1016/j.sab.2010.11.009. DOI

Rehse SJ, Salimnia H, Miziolek AW. Laser-induced breakdown spectroscopy (libs) Journal of Medical Engineering. 2012;36:77–89. PubMed

Santos D, et al. Laser-induced breakdown spectroscopy for analysis of plant materials. Spectrochimica Acta Part B: Atomic Spectroscopy. 2012;71–72:3–13. doi: 10.1016/j.sab.2012.05.005. DOI

Kaiser J, et al. Trace elemental analysis by laser-induced breakdown spectroscopy–biological applications. Surface Science Reports. 2012;67:233–243. doi: 10.1016/j.surfrep.2012.09.001. DOI

Fortes, F. J., Moros, J., Lucena, P., Cabalín, L. M. & Laserna, J. J. Laser-induced breakdown spectroscopy. Analytical Chemistryvol. 85, 640–669 (2013-01-15). PubMed

Harmon RS, Russo RE, Hark RR. Applications of laser-induced breakdown spectroscopy for geochemical and environmental analysis. Spectrochimica Acta Part B: Atomic Spectroscopy. 2013;87:11–26. doi: 10.1016/j.sab.2013.05.017. DOI

Pořízka P, et al. Algal biomass analysis by laser-based analytical techniques—a review. Sensors. 2014;14:17725–17752. doi: 10.3390/s140917725. PubMed DOI PMC

Noll R, et al. Laser-induced breakdown spectroscopy expands into industrial applications. Spectrochimica Acta Part B: Atomic Spectroscopy. 2014;93:41–51. doi: 10.1016/j.sab.2014.02.001. DOI

Windom BC, Hahn DW. Laser ablation–laser induced breakdown spectroscopy (la-libs) Journal of Analytical Atomic Spectrometry. 2009;24:1665–1675. doi: 10.1039/b913495f. DOI

Pořízka P, Klessen B, Kaiser J, Gornushkin I, Panne U. High repetition rate laser-induced breakdown spectroscopy using acousto-optically gated detection. Review of Scientific Instruments. 2014;2014:1–8. PubMed

Andor. Comparing sCMOS. URL http://www.andor.com/learning-academy/comparing-scmos-compare-scmos-with-other-detectors (2017).

QIMAGING. Advances in sCMOS camera technology benefit bio research. URL https://www.qimaging.com/ccdorscmos/pdfs/CCDvsSCMOS.pdf (2017).

Pořízka P, et al. Assessment of the most effective part of echelle laser-induced plasma spectra for further classification using czerny-turner spectrometer. Spectrochimica Acta Part B: Atomic Spectroscopy. 2016;124:116–123. doi: 10.1016/j.sab.2016.09.004. DOI

Brereton, R. G. Applied chemometrics for scientists (John Wiley, Hoboken, NJ, USA, 2007).

Haddad JE, Canioni L, Bousquet B. Good practices in libs analysis. Spectrochimica Acta Part B: Atomic Spectroscopy. 2014;101:171–182. doi: 10.1016/j.sab.2014.08.039. DOI

Pořízka P, et al. Laser-induced breakdown spectroscopy coupled with chemometrics for the analysis of steel; the issue of spectral outliers filtering. Spectrochimica Acta Part B: Atomic Spectroscopy. 2016;123:114–120. doi: 10.1016/j.sab.2016.08.008. DOI

Zorov NB, Gorbatenko AA, Labutin TA, Popov AM. A review of normalization techniques in analytical atomic spectrometry with laser sampling. Spectrochimica Acta Part B: Atomic Spectroscopy. 2010;65:642–657. doi: 10.1016/j.sab.2010.04.009. DOI

Castro JP, Pereira-Filho ER. Twelve different types of data normalization for the proposition of classification, univariate and multivariate regression models for the direct analyses of alloys by laser-induced breakdown spectroscopy (libs) Journal of Analytical Atomic Spectrometry. 2016;31:2005–2014. doi: 10.1039/C6JA00224B. DOI

Pořízka, P. et al. Impact of laser-induced breakdown spectroscopy data normalization on multivariate classification accuracy. Journal of Analytical Atomic Spectrometry article in press (2016).

Lucia FCD, Gottfried JL. Influence of variable selection on partial least squares discriminant analysis models for explosive residue classification. Spectrochimica Acta Part B: Atomic Spectroscopy. 2011;66:122–128. doi: 10.1016/j.sab.2010.12.007. DOI

Klus J, et al. Multivariate approach to the chemical mapping of uranium in sandstone-hosted uranium ores analyzed using double pulse laser-induced breakdown spectroscopy. Spectrochimica Acta Part B. 2016;2016:143–149. doi: 10.1016/j.sab.2016.08.014. DOI

Larsson A, Andersson H, Landström L. Impact of data reduction on multivariate classification models built on spectral data from bio-samples. Journal of Analytical Atomic Spectrometry. 2015;30:1117–1127. doi: 10.1039/C4JA00467A. DOI

Eversberg, T. & Vollmann, K. Spectroscopic instrumentation (Springer, New York, USA, 2014).

Novotný J, et al. A versatile interaction chamber for laser-based spectroscopic applications, with the emphasis on laser-induced breakdown spectroscopy. Spectrochimica Acta Part B: Atomic Spectroscopy. 2014;101:149–154. doi: 10.1016/j.sab.2014.08.004. DOI

Laughlin S. A simple coding procedure enhances a neuron’s information capacity. Zeitschrift für Naturforschung C. 1981;1981:9–10. PubMed

Burges C. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery. 1998;1998:121–167. doi: 10.1023/A:1009715923555. DOI

Fan R, Chang K, Hsieh C, Lin C. Liblinear: A library for large linear classification. Journal of Machine Learning Research. 2008;2008:1871–1874.

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