A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra

Dam-Bé Lardja Douti; Kossi Amouzouvi

doi:doi:10.11648/j.ajmp.20261502.17

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A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra

Dam-Bé Lardja Douti^*

, Kossi Amouzouvi

Published in American Journal of Modern Physics (Volume 15, Issue 2)

Received: 27 February 2026 Accepted: 16 March 2026 Published: 24 April 2026

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Abstract

Laser-Induced Breakdown Spectroscopy (LIBS) has gained interest among analytical techniques the last few years, thanks to its relative simplicity of use: generate compositional information from a material with minimal sample preparation. However, accurate recognition of chemical species in complex mixtures typically requires expert interpretation or extensive calibration datasets, and usually can only be performed on selected chemical elements. To mitigate these limitations and enhance the analytical capability of LIBS, we propose a novel vector space model coupled with singular value decomposition (SVD) and demonstrate its potential for both qualitative and quantitative LIBS analysis. In this vector space based algorithm, each chemical element is encoded as a unit vector; the complete set of unit vectors constitutes a basis that spans the spectral space of any unknown sample. Synthetic spectra generated from the LIBS spectra database of the National Institute of Standards and Technology is used to construct a database of 16 elements and assess the relevance of our approach in the identification and quantification of alloys in LIBS spectra. The algorithm reliably identified all elemental components and estimated their proportions; quantitative precision was highest for simpler binary alloys and decreased with compositional complexity. This approach provides a promising foundation for automated and calibration-light LIBS analysis. The limits of this approach are also discussed and some ideas for improvement are proposed.

Published in	American Journal of Modern Physics (Volume 15, Issue 2)
DOI	10.11648/j.ajmp.20261502.17
Page(s)	62-70
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2026. Published by Science Publishing Group

Keywords

LIBS, Vector Space Model, SVD, Spectral Analysis

References

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Douti, D. L., Amouzouvi, K. (2026). A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra. American Journal of Modern Physics, 15(2), 62-70. https://doi.org/10.11648/j.ajmp.20261502.17

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ACS Style

Douti, D. L.; Amouzouvi, K. A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra. Am. J. Mod. Phys. 2026, 15(2), 62-70. doi: 10.11648/j.ajmp.20261502.17

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AMA Style

Douti DL, Amouzouvi K. A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra. Am J Mod Phys. 2026;15(2):62-70. doi: 10.11648/j.ajmp.20261502.17

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@article{10.11648/j.ajmp.20261502.17,
  author = {Dam-Bé Lardja Douti and Kossi Amouzouvi},
  title = {A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra
},
  journal = {American Journal of Modern Physics},
  volume = {15},
  number = {2},
  pages = {62-70},
  doi = {10.11648/j.ajmp.20261502.17},
  url = {https://doi.org/10.11648/j.ajmp.20261502.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmp.20261502.17},
  abstract = {Laser-Induced Breakdown Spectroscopy (LIBS) has gained interest among analytical techniques the last few years, thanks to its relative simplicity of use: generate compositional information from a material with minimal sample preparation. However, accurate recognition of chemical species in complex mixtures typically requires expert interpretation or extensive calibration datasets, and usually can only be performed on selected chemical elements. To mitigate these limitations and enhance the analytical capability of LIBS, we propose a novel vector space model coupled with singular value decomposition (SVD) and demonstrate its potential for both qualitative and quantitative LIBS analysis. In this vector space based algorithm, each chemical element is encoded as a unit vector; the complete set of unit vectors constitutes a basis that spans the spectral space of any unknown sample. Synthetic spectra generated from the LIBS spectra database of the National Institute of Standards and Technology is used to construct a database of 16 elements and assess the relevance of our approach in the identification and quantification of alloys in LIBS spectra. The algorithm reliably identified all elemental components and estimated their proportions; quantitative precision was highest for simpler binary alloys and decreased with compositional complexity. This approach provides a promising foundation for automated and calibration-light LIBS analysis. The limits of this approach are also discussed and some ideas for improvement are proposed.
},
 year = {2026}
}

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TY  - JOUR
T1  - A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra

AU  - Dam-Bé Lardja Douti
AU  - Kossi Amouzouvi
Y1  - 2026/04/24
PY  - 2026
N1  - https://doi.org/10.11648/j.ajmp.20261502.17
DO  - 10.11648/j.ajmp.20261502.17
T2  - American Journal of Modern Physics
JF  - American Journal of Modern Physics
JO  - American Journal of Modern Physics
SP  - 62
EP  - 70
PB  - Science Publishing Group
SN  - 2326-8891
UR  - https://doi.org/10.11648/j.ajmp.20261502.17
AB  - Laser-Induced Breakdown Spectroscopy (LIBS) has gained interest among analytical techniques the last few years, thanks to its relative simplicity of use: generate compositional information from a material with minimal sample preparation. However, accurate recognition of chemical species in complex mixtures typically requires expert interpretation or extensive calibration datasets, and usually can only be performed on selected chemical elements. To mitigate these limitations and enhance the analytical capability of LIBS, we propose a novel vector space model coupled with singular value decomposition (SVD) and demonstrate its potential for both qualitative and quantitative LIBS analysis. In this vector space based algorithm, each chemical element is encoded as a unit vector; the complete set of unit vectors constitutes a basis that spans the spectral space of any unknown sample. Synthetic spectra generated from the LIBS spectra database of the National Institute of Standards and Technology is used to construct a database of 16 elements and assess the relevance of our approach in the identification and quantification of alloys in LIBS spectra. The algorithm reliably identified all elemental components and estimated their proportions; quantitative precision was highest for simpler binary alloys and decreased with compositional complexity. This approach provides a promising foundation for automated and calibration-light LIBS analysis. The limits of this approach are also discussed and some ideas for improvement are proposed.

VL  - 15
IS  - 2
ER  -

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Author Information

Dam-Bé Lardja Douti

Laboratoire Matériaux Energies Renouvelables et Environnement / Université de Kara, Kara, Togo

Contact Email

http://orcid.org/0009-0002-9534-051X
Kossi Amouzouvi

Center for Scalable Data Analytics and AI (ScaDS. AI) Dresden/Technical University of Dresden, Dresden, Germany; Department of Mathematics/Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

Contact Email

http://orcid.org/0000-0002-3614-0449

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APA Style

Douti, D. L., Amouzouvi, K. (2026). A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra. American Journal of Modern Physics, 15(2), 62-70. https://doi.org/10.11648/j.ajmp.20261502.17

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ACS Style

Douti, D. L.; Amouzouvi, K. A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra. Am. J. Mod. Phys. 2026, 15(2), 62-70. doi: 10.11648/j.ajmp.20261502.17

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AMA Style

Douti DL, Amouzouvi K. A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra. Am J Mod Phys. 2026;15(2):62-70. doi: 10.11648/j.ajmp.20261502.17

Copy | Download

@article{10.11648/j.ajmp.20261502.17,
  author = {Dam-Bé Lardja Douti and Kossi Amouzouvi},
  title = {A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra
},
  journal = {American Journal of Modern Physics},
  volume = {15},
  number = {2},
  pages = {62-70},
  doi = {10.11648/j.ajmp.20261502.17},
  url = {https://doi.org/10.11648/j.ajmp.20261502.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmp.20261502.17},
  abstract = {Laser-Induced Breakdown Spectroscopy (LIBS) has gained interest among analytical techniques the last few years, thanks to its relative simplicity of use: generate compositional information from a material with minimal sample preparation. However, accurate recognition of chemical species in complex mixtures typically requires expert interpretation or extensive calibration datasets, and usually can only be performed on selected chemical elements. To mitigate these limitations and enhance the analytical capability of LIBS, we propose a novel vector space model coupled with singular value decomposition (SVD) and demonstrate its potential for both qualitative and quantitative LIBS analysis. In this vector space based algorithm, each chemical element is encoded as a unit vector; the complete set of unit vectors constitutes a basis that spans the spectral space of any unknown sample. Synthetic spectra generated from the LIBS spectra database of the National Institute of Standards and Technology is used to construct a database of 16 elements and assess the relevance of our approach in the identification and quantification of alloys in LIBS spectra. The algorithm reliably identified all elemental components and estimated their proportions; quantitative precision was highest for simpler binary alloys and decreased with compositional complexity. This approach provides a promising foundation for automated and calibration-light LIBS analysis. The limits of this approach are also discussed and some ideas for improvement are proposed.
},
 year = {2026}
}

Copy | Download

TY  - JOUR
T1  - A Vector Space Model Based Algorithm for Element Identification in Laser Induced Breakdown Spectroscopy Spectra

AU  - Dam-Bé Lardja Douti
AU  - Kossi Amouzouvi
Y1  - 2026/04/24
PY  - 2026
N1  - https://doi.org/10.11648/j.ajmp.20261502.17
DO  - 10.11648/j.ajmp.20261502.17
T2  - American Journal of Modern Physics
JF  - American Journal of Modern Physics
JO  - American Journal of Modern Physics
SP  - 62
EP  - 70
PB  - Science Publishing Group
SN  - 2326-8891
UR  - https://doi.org/10.11648/j.ajmp.20261502.17
AB  - Laser-Induced Breakdown Spectroscopy (LIBS) has gained interest among analytical techniques the last few years, thanks to its relative simplicity of use: generate compositional information from a material with minimal sample preparation. However, accurate recognition of chemical species in complex mixtures typically requires expert interpretation or extensive calibration datasets, and usually can only be performed on selected chemical elements. To mitigate these limitations and enhance the analytical capability of LIBS, we propose a novel vector space model coupled with singular value decomposition (SVD) and demonstrate its potential for both qualitative and quantitative LIBS analysis. In this vector space based algorithm, each chemical element is encoded as a unit vector; the complete set of unit vectors constitutes a basis that spans the spectral space of any unknown sample. Synthetic spectra generated from the LIBS spectra database of the National Institute of Standards and Technology is used to construct a database of 16 elements and assess the relevance of our approach in the identification and quantification of alloys in LIBS spectra. The algorithm reliably identified all elemental components and estimated their proportions; quantitative precision was highest for simpler binary alloys and decreased with compositional complexity. This approach provides a promising foundation for automated and calibration-light LIBS analysis. The limits of this approach are also discussed and some ideas for improvement are proposed.

VL  - 15
IS  - 2
ER  -

Copy | Download