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Spectral library transfer between distinct Laser-Induced Breakdown Spectroscopy systems trained on simultaneous measurements

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F23%3APU147758" target="_blank" >RIV/00216305:26620/23:PU147758 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/00216224:14310/23:00132292

  • Výsledek na webu

    <a href="https://pubs.rsc.org/en/content/articlelanding/2023/ja/d2ja00406b" target="_blank" >https://pubs.rsc.org/en/content/articlelanding/2023/ja/d2ja00406b</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1039/D2JA00406B" target="_blank" >10.1039/D2JA00406B</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Spectral library transfer between distinct Laser-Induced Breakdown Spectroscopy systems trained on simultaneous measurements

  • Popis výsledku v původním jazyce

    The mutual incompatibility of distinct spectroscopic systems is among the most limiting factors in Laser-Induced Breakdown Spectroscopy (LIBS). The cost related to setting up a new LIBS system is increased, as its extensive calibration is required. Solving the problem would enable inter-laboratory reference measurements and shared spectral libraries, which are fundamental for other spectroscopic techniques. We study a simplified version of this challenge where LIBS systems differ only in used spectrometers and collection optics but share all other parts of the apparatus, and collect spectra simultaneously from the same plasma plume. Extensive datasets measured as hyperspectral images of heterogeneous rock sample are used to train machine learning models that can transfer spectra between systems. The transfer is realized by a composed model that consists of a variational autoencoder (VAE) and a multilayer perceptron (MLP). The VAE is used to create a latent representation of spectra from the Primary system. Subsequently, spectra from the Secondary system are mapped to corresponding locations in the latent space by the MLP. The transfer is evaluated by several figures of merit (Euclidean and cosine distances, both spatially resolved; k-means clustering of transferred spectra). We demonstrate the viability of the method and compare it to several baseline approaches of varying complexity.

  • Název v anglickém jazyce

    Spectral library transfer between distinct Laser-Induced Breakdown Spectroscopy systems trained on simultaneous measurements

  • Popis výsledku anglicky

    The mutual incompatibility of distinct spectroscopic systems is among the most limiting factors in Laser-Induced Breakdown Spectroscopy (LIBS). The cost related to setting up a new LIBS system is increased, as its extensive calibration is required. Solving the problem would enable inter-laboratory reference measurements and shared spectral libraries, which are fundamental for other spectroscopic techniques. We study a simplified version of this challenge where LIBS systems differ only in used spectrometers and collection optics but share all other parts of the apparatus, and collect spectra simultaneously from the same plasma plume. Extensive datasets measured as hyperspectral images of heterogeneous rock sample are used to train machine learning models that can transfer spectra between systems. The transfer is realized by a composed model that consists of a variational autoencoder (VAE) and a multilayer perceptron (MLP). The VAE is used to create a latent representation of spectra from the Primary system. Subsequently, spectra from the Secondary system are mapped to corresponding locations in the latent space by the MLP. The transfer is evaluated by several figures of merit (Euclidean and cosine distances, both spatially resolved; k-means clustering of transferred spectra). We demonstrate the viability of the method and compare it to several baseline approaches of varying complexity.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    10406 - Analytical chemistry

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/EF19_073%2F0016948" target="_blank" >EF19_073/0016948: Kvalitní interní granty VUT</a><br>

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2023

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Journal of Analytical Atomic Spectrometry

  • ISSN

    0267-9477

  • e-ISSN

    1364-5544

  • Svazek periodika

    38

  • Číslo periodika v rámci svazku

    4

  • Stát vydavatele periodika

    GB - Spojené království Velké Británie a Severního Irska

  • Počet stran výsledku

    12

  • Strana od-do

    841-853

  • Kód UT WoS článku

    000940533400001

  • EID výsledku v databázi Scopus

    2-s2.0-85149255901