| Issue |
J. Eur. Opt. Soc.-Rapid Publ.
Volume 3, 2008
|
|
|---|---|---|
| Article Number | 08011 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.2971/jeos.2008.08011 | |
| Published online | 06 March 2008 | |
Regular papers
Quantitative multi-elemental laser-induced breakdown spectroscopy using artificial neural networks
1
Canadian Space Agency, 6767 Route de l’Aéroport, Longueuil, Québec, Canada J3Y 8Y9
2
Current address: Department of Earth Sciences/Department of Physics and Astronomy, University of Western Ontario, 1151 Richmond Street, London, Ontario, N6A 5B7 Canada
* alexander.koujelev@space.gc.ca
Received:
26
October
2007
The Laser-Induced Breakdown Spectroscopy (LIBS) is an emerging technique with great potential in atomic elemental analysis in many areas, particularly, in space exploration. In this paper, an algorithm for automated identification of elements and measurements of their concentrations in rocks and soils, as well as its experimental validation are presented. The proposed approach is based on the artificial neural network (ANN). We demonstrate that the ANN algorithm works successfully for all major elements of geological interest tested on natural rock and soil samples.
Key words: Laser-induced breakdown spectroscopy (LIBS) / artificial neural network (ANN) / quantitative spectroscopy of minerals / laser instrumentation for planetary exploration
© The Author(s) 2008. All rights reserved.
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