Multi-elemental analysis of solidified mineral melt samples by laser-induced breakdown spectroscopy coupled with a linear multivariate calibration

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DOIResolve DOI: http://doi.org/10.1016/j.sab.2007.10.003
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TypeArticle
Journal titleSpectrochimica Acta Part B: Atomic Spectroscopy
Volume62
Issue12
Pages15571566; # of pages: 10
SubjectLaser-induced breakdown spectroscopy; Glass analysis; Multivariate inverse calibration
AbstractLaser-Induced Breakdown Spectroscopy (LIBS) has been successfully applied for multi-elemental analysis of solidified mineral melt samples containing several oxides present in various concentrations. The plasma was generated using a Nd:YAG laser and the spectra were acquired using an Echelle spectrometer, coupled to an ICCD detector, which covers a spectral range from 200 to 780 nm. Using a set of 19 calibration samples, we first established univariate calibration curves for the major elements (Al, Fe, Mg, Ca, Ti and Si). We found out that the presence of matrix effects makes such a model, traditionally used in LIBS, not satisfying for quantitative analysis of such samples. Indeed, no sufficiently linear trends can be extracted from the calibration curves for the elements of interest considering all the samples. Instead, a much more robust calibration approach was obtained by considering a multivariate model. The matrix effects are then taken into account by correcting the spectroscopic signals emitted by a given species due the presence of the others ones. More specifically, we established here a calibration model using a 2nd order polynomial linear multivariate inverse regression. The capability of this approach was then checked using a 2nd set of samples with an unknown composition. A good agreement was observed between the analysis provided by X-ray fluorescence (XRF) and the LIBS measurements coupled to the multivariate model for the unknown samples.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada (NRC-CNRC); NRC Industrial Materials Institute
Peer reviewedYes
NRC number53653
NPARC number15825972
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Record identifier84addb28-476b-42ac-8e18-5b9894b2fd2a
Record created2010-07-20
Record modified2016-05-09
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