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ANN-LIBS analysis of mixture plasmas: detection of xenon

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    SYSNO ASEP0559890
    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, Homa (UFCH-W) ORCID, RID
    Myakalwar, A. K. (CL)
    Kubelík, Petr (UFCH-W) RID, ORCID
    Ghaderi, A. (CA)
    Laitl, Vojtěch (UFCH-W) ORCID
    Petera, Lukáš (UFCH-W) ORCID
    Rimmer, P. B. (GB)
    Shorttle, O. (GB)
    Heays, Alan (UFCH-W) ORCID, RID, SAI
    Křivková, Anna (UFCH-W) ORCID
    Krůs, Miroslav (UFP-V) RID
    Civiš, Svatopluk (UFCH-W) RID, ORCID, SAI
    Yanez, J. (CL)
    Kepes, E. (CZ)
    Pořízka, P. (CZ)
    Ferus, Martin (UFCH-W) ORCID, RID
    Source TitleJournal of Analytical Atomic Spectrometry. - : Royal Society of Chemistry - ISSN 0267-9477
    Roč. 37, č. 9 (2022), s. 1815-1823
    Number of pages9 s.
    Languageeng - English
    CountryGB - United Kingdom
    KeywordsANN-LIBS analysis ; xenon ; planetary processes
    Subject RIVCF - Physical ; Theoretical Chemistry
    OECD categoryPhysical chemistry
    Subject RIV - cooperationInstitute of Plasma Physics - Plasma and Gas Discharge Physics
    R&D ProjectsGA21-11366S GA ČR - Czech Science Foundation (CSF)
    EF16_019/0000778 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    Method of publishingLimited access
    Institutional supportUFCH-W - RVO:61388955 ; UFP-V - RVO:61389021
    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. The method can be used for determination of Xe plasma physical parameters in industrial as well as scientific applications.
    WorkplaceJ. Heyrovsky Institute of Physical Chemistry
    ContactMichaela Knapová, michaela.knapova@jh-inst.cas.cz, Tel.: 266 053 196
    Year of Publishing2023
    Electronic addresshttps://hdl.handle.net/11104/0333017
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