Critical review and advices on spectral-based normalization methods for LIBS quantitative analysis
GUÉZÉNOC, Julian
Interactions Sol Plante Atmosphère [UMR ISPA]
Centre d'Etudes Lasers Intenses et Applications [CELIA]
Interactions Sol Plante Atmosphère [UMR ISPA]
Centre d'Etudes Lasers Intenses et Applications [CELIA]
GUÉZÉNOC, Julian
Interactions Sol Plante Atmosphère [UMR ISPA]
Centre d'Etudes Lasers Intenses et Applications [CELIA]
< Réduire
Interactions Sol Plante Atmosphère [UMR ISPA]
Centre d'Etudes Lasers Intenses et Applications [CELIA]
Langue
en
Article de revue
Ce document a été publié dans
Spectrochimica Acta Part B: Atomic Spectroscopy. 2019, vol. 160, p. 1-8
Elsevier
Résumé en anglais
As it is the case for any spectroscopic technique, laser-induced breakdown spectroscopy (LIBS) is strongly influenced by the signal fluctuations, and the LIBS spectra need to be normalized to obtain enhanced analytical ...Lire la suite >
As it is the case for any spectroscopic technique, laser-induced breakdown spectroscopy (LIBS) is strongly influenced by the signal fluctuations, and the LIBS spectra need to be normalized to obtain enhanced analytical performance. Nowadays, normalization in LIBS remains an open question and, in the present review, the normalization methods commonly applied to LIBS are presented and discussed, in particular those based on background, total area, internal standard, and Standard Normal Variate. We emphasize that the figures of merit, namely the coefficient of determination, the root-mean square error of prediction and the limit of quantification used to assess the advantages of processing normalized instead of non-normalized LIBS spectra, in a context of quantification, must be calculated in a rigorous way to be able to draw conclusions. We thus propose advices and good practices to achieve a rigorous comparison between quantitative models involving various normalization approaches, the final choice of the best normalization being ultimately driven by the analytical context. In order to take the best advantage from normalization in LIBS and thus increase the analytical performance of this technique, we encourage the analyst to thoroughly compare different normalization methods.< Réduire
Mots clés
LIBS
assessment
Mots clés en anglais
normalization
good practices
figures of merit
Origine
Importé de halUnités de recherche