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ANN-LIBS analysis of mixture plasmas: detection of xenon

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    SYSNO ASEP0579026
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleANN-LIBS analysis of mixture plasmas: detection of xenon
    Author(s) Saeidfirozeh, H. (CZ)
    Myakalwar, A. K. (CL)
    Kubelík, Petr (FZU-D) RID, ORCID
    Ghaderi, A. (CA)
    Laitl, V. (CZ)
    Petera, L. (CZ)
    Rimmer, P. B. (GB)
    Shorttle, O. (GB)
    Heays, A.N. (CZ)
    Křivková, A. (CZ)
    Krůs, M. (CZ)
    Civiš, S. (CZ)
    Yanez, J. (CL)
    Képeš, E. (CZ)
    Pořízka, P. (CZ)
    Ferus, M. (CZ)
    Number of authors16
    Source TitleJournal of Analytical Atomic Spectrometry. - : Royal Society of Chemistry - ISSN 0267-9477
    Roč. 37, č. 9 (2022), s. 1815-1823
    Number of pages10 s.
    Languageeng - English
    CountryGB - United Kingdom
    Keywordsartificial neural network method ; characterising crucial physical plasma parameters ; laser-induced breakdown spectra, ; xenon
    Subject RIVBL - Plasma and Gas Discharge Physics
    OECD categoryFluids and plasma physics (including surface physics)
    Method of publishingLimited access
    Institutional supportFZU-D - RVO:68378271
    UT WOS000826342300001
    EID SCOPUS85134913156
    DOI10.1039/d2ja00132b
    AnnotationWe developed an artificial neural network method for characterising crucial physical plasma parameters (i.e., temperature, electron density, and abundance ratios of ionisation states) in a fast and precise manner that mitigates common issues arising in evaluation of laser-induced breakdown spectra. The neural network was trained on a set of laser-induced breakdown spectra of xenon, a particularly physically and geochemically intriguing noble gas. The artificial neural network results were subsequently compared to a standard local thermodynamic equilibrium model. Speciation analysis of Xe was performed in a model atmosphere, mimicking gaseous systems relevant for tracing noble gases in geochemistry. The results demonstrate a comprehensive method for geochemical analyses, particularly a new concept of Xe detection in geochemical systems with an order-of-magnitude speed enhancement and requiring minimal input information.
    WorkplaceInstitute of Physics
    ContactKristina Potocká, potocka@fzu.cz, Tel.: 220 318 579
    Year of Publishing2024
    Electronic addresshttps://doi.org/10.1039/d2ja00132b
Number of the records: 1  

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