Many-to-many transfer of LIBS spectra across multiple experimental conditions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F26%3A0201185" target="_blank" >RIV/00216305:26620/26:0201185 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1039/D5JA00401B" target="_blank" >https://doi.org/10.1039/D5JA00401B</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1039/d5ja00401b" target="_blank" >10.1039/d5ja00401b</a>

Result language

angličtina

Original language name

Many-to-many transfer of LIBS spectra across multiple experimental conditions

Original language description

Laser-Induced Breakdown Spectroscopy (LIBS) is a powerful analytical technique widely used for extraterrestrial remote analysis. However useful, its primary limitation is its sensitivity to measurement conditions, making direct data transfer (DT) between LIBS systems with different analytical systems impractical. Addressing this challenge directly would require costly studies, extensive sample analysis or simulations of plasma formation in different atmospheres, moreover this approach would demand extensive calibration across various LIBS systems. Previous studies have demonstrated that machine learning models can facilitate DT across different instruments and conditions. However, existing approaches either rely on one-to-one spectral pairs or are limited to predefined condition pairs. We propose an alternative solution: a single machine learning model capable of many-to-many transfer across multiple conditions without requiring both one-to-one spectral representations and huge amounts of data. Our model has been trained on regolith LIBS spectra, measured in-house across two simulated atmospheres (Earth, Moon/vacuum) and with two laser energies (30 and 15 mJ). The model evaluation focuses on the Root Mean Square Error (RMSE) of predicted elemental concentrations from transformed spectra, serving as the primary metric for the transfer quality. The proposed model for which task outperforms Piecewise Direct Standardization (PDS) based baseline approaches by around 10% in terms of RMSE.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10406 - Analytical chemistry

Project

<a href="/en/project/GF23-05186K" target="_blank" >GF23-05186K: Characterization of laser-induced plasmas under simulated conditions of selected celestial bodies</a><br>

Continuities

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

Publication year

2026

Confidentiality

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

Name of the periodical

JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY

ISSN

0267-9477

e-ISSN

1364-5544

Volume of the periodical

—

Issue of the periodical within the volume

41

Country of publishing house

GB - UNITED KINGDOM

Number of pages

8

Pages from-to

593-600

UT code for WoS article

001668274600001

EID of the result in the Scopus database

2-s2.0-105028101800