1. Detection of minor compounds in complex mineral samples from millions of spectra: A new data analysis strategy in LIBS imaging
- Author
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Ludovic Duponchel, Frédéric Pelascini, Cécile Fabre, Jean Cauzid, Vincent Motto-Ros, Alessandro Nardecchia, Laboratoire Avancé de Spectroscopie pour les Intéractions la Réactivité et l'Environnement - UMR 8516 (LASIRE), Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), GeoRessources, Institut national des sciences de l'Univers (INSU - CNRS)-Centre de recherches sur la géologie des matières premières minérales et énergétiques (CREGU)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Cetim Grand Est, Spectrométrie des biomolécules et agrégats (SPECTROBIO), Institut Lumière Matière [Villeurbanne] (ILM), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Pulsalys, French region Grand Est, French region Rhones Alpes Auvergne (Optolyse, CPER2016), Institut de Chimie du CNRS (INC)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille Institut (CLIL), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre de recherches sur la géologie des matières premières minérales et énergétiques (CREGU)-Institut national des sciences de l'Univers (INSU - CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon
- Subjects
Chemical imaging ,Hyperspectral imaging ,Field of view ,02 engineering and technology ,01 natural sciences ,Biochemistry ,Clustering ,Spectral line ,Analytical Chemistry ,Big data ,[SPI]Engineering Sciences [physics] ,[CHIM]Chemical Sciences ,Environmental Chemistry ,Spectroscopy ,Cluster analysis ,[PHYS]Physics [physics] ,Detection limit ,business.industry ,Chemistry ,010401 analytical chemistry ,Pattern recognition ,021001 nanoscience & nanotechnology ,0104 chemical sciences ,Characterization (materials science) ,Laser-induced breakdown spectroscopy (LIBS) ,Artificial intelligence ,0210 nano-technology ,business - Abstract
International audience; Today, Laser-Induced Breakdown Spectroscopy (LIBS) imaging is in full change. Indeed, always more stable instrumentations are developed, which significantly increases the signal quality and naturally the analytical potential of the technique for the characterization of complex and heterogeneous samples at the micro-scale level. Obviously, other intrinsic features such as a limit of detection in the order of ppm, a high field of view and high acquisition rate make it one of the most complete chemical imaging techniques to date. It is thus possible in these conditions to acquire several million spectra from one single sample in just hours. Managing big data in LIBS imaging is the challenge ahead. In this paper, we put forward a new spectral analysis strategy, called embedded k-means clustering, for simultaneous detection of major and minor compounds and the generation of associated localization maps. A complex rock section with different phases and traces will be explored to demonstrate the value of this approach.
- Published
- 2020
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