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Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements

We report on the use of quartz-enhanced photoacoustic spectroscopy (QEPAS) for multi-gas detection. Photoacoustic (PA) spectra of mixtures of water (H [Formula: see text] O), ammonia (NH [Formula: see text]), and methane (CH [Formula: see text]) were measured in the mid-infrared (MIR) wavelength ran...

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Autores principales: Rasmussen, Andreas N., Thomsen, Benjamin L., Christensen, Jesper B., Petersen, Jan C., Lassen, Mikael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537676/
https://www.ncbi.nlm.nih.gov/pubmed/37766039
http://dx.doi.org/10.3390/s23187984
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author Rasmussen, Andreas N.
Thomsen, Benjamin L.
Christensen, Jesper B.
Petersen, Jan C.
Lassen, Mikael
author_facet Rasmussen, Andreas N.
Thomsen, Benjamin L.
Christensen, Jesper B.
Petersen, Jan C.
Lassen, Mikael
author_sort Rasmussen, Andreas N.
collection PubMed
description We report on the use of quartz-enhanced photoacoustic spectroscopy (QEPAS) for multi-gas detection. Photoacoustic (PA) spectra of mixtures of water (H [Formula: see text] O), ammonia (NH [Formula: see text]), and methane (CH [Formula: see text]) were measured in the mid-infrared (MIR) wavelength range using a mid-infrared (MIR) optical parametric oscillator (OPO) light source. Highly overlapping absorption spectra are a common challenge for gas spectroscopy. To mitigate this, we used a partial least-squares regression (PLS) method to estimate the mixing ratio and concentrations of the individual gasses. The concentration range explored in the analysis varies from a few parts per million (ppm) to thousands of ppm. Spectra obtained from HITRAN and experimental single-molecule reference spectra of each of the molecular species were acquired and used as training data sets. These spectra were used to generate simulated spectra of the gas mixtures (linear combinations of the reference spectra). Here, in this proof-of-concept experiment, we demonstrate that after an absolute calibration of the QEPAS cell, the PLS analyses could be used to determine concentrations of single molecular species with a relative accuracy within a few % for mixtures of H [Formula: see text] O, NH [Formula: see text] , and CH [Formula: see text] and with an absolute sensitivity of approximately 300 (±50) ppm/V, 50 (±5) ppm/V, and 5 (±2) ppm/V for water, ammonia, and methane, respectively. This demonstrates that QEPAS assisted by PLS is a powerful approach to estimate concentrations of individual gas components with considerable spectral overlap, which is a typical scenario for real-life adoptions and applications.
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spelling pubmed-105376762023-09-29 Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements Rasmussen, Andreas N. Thomsen, Benjamin L. Christensen, Jesper B. Petersen, Jan C. Lassen, Mikael Sensors (Basel) Article We report on the use of quartz-enhanced photoacoustic spectroscopy (QEPAS) for multi-gas detection. Photoacoustic (PA) spectra of mixtures of water (H [Formula: see text] O), ammonia (NH [Formula: see text]), and methane (CH [Formula: see text]) were measured in the mid-infrared (MIR) wavelength range using a mid-infrared (MIR) optical parametric oscillator (OPO) light source. Highly overlapping absorption spectra are a common challenge for gas spectroscopy. To mitigate this, we used a partial least-squares regression (PLS) method to estimate the mixing ratio and concentrations of the individual gasses. The concentration range explored in the analysis varies from a few parts per million (ppm) to thousands of ppm. Spectra obtained from HITRAN and experimental single-molecule reference spectra of each of the molecular species were acquired and used as training data sets. These spectra were used to generate simulated spectra of the gas mixtures (linear combinations of the reference spectra). Here, in this proof-of-concept experiment, we demonstrate that after an absolute calibration of the QEPAS cell, the PLS analyses could be used to determine concentrations of single molecular species with a relative accuracy within a few % for mixtures of H [Formula: see text] O, NH [Formula: see text] , and CH [Formula: see text] and with an absolute sensitivity of approximately 300 (±50) ppm/V, 50 (±5) ppm/V, and 5 (±2) ppm/V for water, ammonia, and methane, respectively. This demonstrates that QEPAS assisted by PLS is a powerful approach to estimate concentrations of individual gas components with considerable spectral overlap, which is a typical scenario for real-life adoptions and applications. MDPI 2023-09-20 /pmc/articles/PMC10537676/ /pubmed/37766039 http://dx.doi.org/10.3390/s23187984 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Rasmussen, Andreas N.
Thomsen, Benjamin L.
Christensen, Jesper B.
Petersen, Jan C.
Lassen, Mikael
Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements
title Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements
title_full Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements
title_fullStr Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements
title_full_unstemmed Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements
title_short Quartz-Enhanced Photoacoustic Spectroscopy Assisted by Partial Least-Squares Regression for Multi-Gas Measurements
title_sort quartz-enhanced photoacoustic spectroscopy assisted by partial least-squares regression for multi-gas measurements
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10537676/
https://www.ncbi.nlm.nih.gov/pubmed/37766039
http://dx.doi.org/10.3390/s23187984
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