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Real-time gas mass spectroscopy by multivariate analysis

Early and significant results for a real-time, column-free miniaturized gas mass spectrometer in detecting target species with partial overlapping spectra are reported. The achievements have been made using both nanoscale holes as a nanofluidic sampling inlet system and a robust statistical techniqu...

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Autores principales: Franceschelli, Leonardo, Ciricugno, Carla, Di Lorenzo, Maurizio, Romani, Aldo, Berardinelli, Annachiara, Tartagni, Marco, Correale, Raffaele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10101983/
https://www.ncbi.nlm.nih.gov/pubmed/37055471
http://dx.doi.org/10.1038/s41598-023-33188-x
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author Franceschelli, Leonardo
Ciricugno, Carla
Di Lorenzo, Maurizio
Romani, Aldo
Berardinelli, Annachiara
Tartagni, Marco
Correale, Raffaele
author_facet Franceschelli, Leonardo
Ciricugno, Carla
Di Lorenzo, Maurizio
Romani, Aldo
Berardinelli, Annachiara
Tartagni, Marco
Correale, Raffaele
author_sort Franceschelli, Leonardo
collection PubMed
description Early and significant results for a real-time, column-free miniaturized gas mass spectrometer in detecting target species with partial overlapping spectra are reported. The achievements have been made using both nanoscale holes as a nanofluidic sampling inlet system and a robust statistical technique. Even if the presented physical implementation could be used with gas chromatography columns, the aim of high miniaturization requires investigating its detection performance with no aid. As a study case, in the first experiment, dichloromethane (CH(2)Cl(2)) and cyclohexane (C(6)H(12)) with concentrations in the 6–93 ppm range in single and compound mixtures were used. The nano-orifice column-free approach acquired raw spectra in 60 s with correlation coefficients of 0.525 and 0.578 to the NIST reference database, respectively. Then, we built a calibration dataset on 320 raw spectra of 10 known different blends of these two compounds using partial least square regression (PLSR) for statistical data inference. The model showed a normalized full-scale root-mean-square deviation (NRMSD) accuracy of [Formula: see text] and [Formula: see text] for each species, respectively, even in combined mixtures. A second experiment was conducted on mixes containing two other gasses, Xylene and Limonene, acting as interferents. Further 256 spectra were acquired on 8 new mixes, from which two models were developed to predict CH(2)Cl(2) and C(6)H(12), obtaining NRMSD values of 6.4% and 13.9%, respectively.
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spelling pubmed-101019832023-04-15 Real-time gas mass spectroscopy by multivariate analysis Franceschelli, Leonardo Ciricugno, Carla Di Lorenzo, Maurizio Romani, Aldo Berardinelli, Annachiara Tartagni, Marco Correale, Raffaele Sci Rep Article Early and significant results for a real-time, column-free miniaturized gas mass spectrometer in detecting target species with partial overlapping spectra are reported. The achievements have been made using both nanoscale holes as a nanofluidic sampling inlet system and a robust statistical technique. Even if the presented physical implementation could be used with gas chromatography columns, the aim of high miniaturization requires investigating its detection performance with no aid. As a study case, in the first experiment, dichloromethane (CH(2)Cl(2)) and cyclohexane (C(6)H(12)) with concentrations in the 6–93 ppm range in single and compound mixtures were used. The nano-orifice column-free approach acquired raw spectra in 60 s with correlation coefficients of 0.525 and 0.578 to the NIST reference database, respectively. Then, we built a calibration dataset on 320 raw spectra of 10 known different blends of these two compounds using partial least square regression (PLSR) for statistical data inference. The model showed a normalized full-scale root-mean-square deviation (NRMSD) accuracy of [Formula: see text] and [Formula: see text] for each species, respectively, even in combined mixtures. A second experiment was conducted on mixes containing two other gasses, Xylene and Limonene, acting as interferents. Further 256 spectra were acquired on 8 new mixes, from which two models were developed to predict CH(2)Cl(2) and C(6)H(12), obtaining NRMSD values of 6.4% and 13.9%, respectively. Nature Publishing Group UK 2023-04-13 /pmc/articles/PMC10101983/ /pubmed/37055471 http://dx.doi.org/10.1038/s41598-023-33188-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Franceschelli, Leonardo
Ciricugno, Carla
Di Lorenzo, Maurizio
Romani, Aldo
Berardinelli, Annachiara
Tartagni, Marco
Correale, Raffaele
Real-time gas mass spectroscopy by multivariate analysis
title Real-time gas mass spectroscopy by multivariate analysis
title_full Real-time gas mass spectroscopy by multivariate analysis
title_fullStr Real-time gas mass spectroscopy by multivariate analysis
title_full_unstemmed Real-time gas mass spectroscopy by multivariate analysis
title_short Real-time gas mass spectroscopy by multivariate analysis
title_sort real-time gas mass spectroscopy by multivariate analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10101983/
https://www.ncbi.nlm.nih.gov/pubmed/37055471
http://dx.doi.org/10.1038/s41598-023-33188-x
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