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Rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy

Use of e-cigarettes is increasing, alongside an expanding variety of devices and e-liquids. To match this growth and in line with the expanding legal and regulatory requirements applicable to manufacturers of e-cigarettes (e.g. disclosure of list of ingredients and quantities thereof in a product),...

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Autores principales: Hoffmann, Anaïs R. F., Jeffery, Jana, Dallin, Paul, Andrews, John, Brokl, Michał
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439909/
https://www.ncbi.nlm.nih.gov/pubmed/37598198
http://dx.doi.org/10.1038/s41598-023-40422-z
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author Hoffmann, Anaïs R. F.
Jeffery, Jana
Dallin, Paul
Andrews, John
Brokl, Michał
author_facet Hoffmann, Anaïs R. F.
Jeffery, Jana
Dallin, Paul
Andrews, John
Brokl, Michał
author_sort Hoffmann, Anaïs R. F.
collection PubMed
description Use of e-cigarettes is increasing, alongside an expanding variety of devices and e-liquids. To match this growth and in line with the expanding legal and regulatory requirements applicable to manufacturers of e-cigarettes (e.g. disclosure of list of ingredients and quantities thereof in a product), rapid methods for determining levels of the main e-liquid constituents—namely, propylene glycol (PG), vegetable glycerol (VG), water and nicotine—are needed. We have assessed the ability of near infrared (NIR) spectroscopy, coupled with partial least squares (PLS) regression, to predict the levels of these constituents in e-liquid formulations. Using NIR spectral data from a large set of reference e-liquids incorporating working concentration ranges, flavourings, and other ingredients, linear calibration models were established for PG, VG, water and nicotine (predicted vs theoretical values, all R(2) > 0.995). The performance of these models was then evaluated on commercial e-liquids using NIR and compared to results obtained by gas chromatography (GC). A strong correlation was observed between NIR-predicted values and measured values for PG, VG and nicotine (all R(2) > 0.955). There was less consistency between predicted and GC measured values for water due to the relatively high limit of quantification (LOQ) of the GC method (2.6% w/w) versus the e-liquid content (0–18% w/w). The LOQ of the NIR method for water was 0.6% w/w, suggesting that NIR may be a more accurate method than GC to predict water concentration in e-liquids, especially at low levels (< 2.6% w/w). Collectively, although limitations of the technique have been identified, specifically for e-liquids containing compounds that might interfere with the set calibrations, our findings suggest that NIR combined with PLS regression is a suitable tool for rapid, simultaneous and high-throughput measurement of PG, VG, water and nicotine levels in most commercial e-liquids.
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spelling pubmed-104399092023-08-21 Rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy Hoffmann, Anaïs R. F. Jeffery, Jana Dallin, Paul Andrews, John Brokl, Michał Sci Rep Article Use of e-cigarettes is increasing, alongside an expanding variety of devices and e-liquids. To match this growth and in line with the expanding legal and regulatory requirements applicable to manufacturers of e-cigarettes (e.g. disclosure of list of ingredients and quantities thereof in a product), rapid methods for determining levels of the main e-liquid constituents—namely, propylene glycol (PG), vegetable glycerol (VG), water and nicotine—are needed. We have assessed the ability of near infrared (NIR) spectroscopy, coupled with partial least squares (PLS) regression, to predict the levels of these constituents in e-liquid formulations. Using NIR spectral data from a large set of reference e-liquids incorporating working concentration ranges, flavourings, and other ingredients, linear calibration models were established for PG, VG, water and nicotine (predicted vs theoretical values, all R(2) > 0.995). The performance of these models was then evaluated on commercial e-liquids using NIR and compared to results obtained by gas chromatography (GC). A strong correlation was observed between NIR-predicted values and measured values for PG, VG and nicotine (all R(2) > 0.955). There was less consistency between predicted and GC measured values for water due to the relatively high limit of quantification (LOQ) of the GC method (2.6% w/w) versus the e-liquid content (0–18% w/w). The LOQ of the NIR method for water was 0.6% w/w, suggesting that NIR may be a more accurate method than GC to predict water concentration in e-liquids, especially at low levels (< 2.6% w/w). Collectively, although limitations of the technique have been identified, specifically for e-liquids containing compounds that might interfere with the set calibrations, our findings suggest that NIR combined with PLS regression is a suitable tool for rapid, simultaneous and high-throughput measurement of PG, VG, water and nicotine levels in most commercial e-liquids. Nature Publishing Group UK 2023-08-19 /pmc/articles/PMC10439909/ /pubmed/37598198 http://dx.doi.org/10.1038/s41598-023-40422-z 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
Hoffmann, Anaïs R. F.
Jeffery, Jana
Dallin, Paul
Andrews, John
Brokl, Michał
Rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy
title Rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy
title_full Rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy
title_fullStr Rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy
title_full_unstemmed Rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy
title_short Rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy
title_sort rapid determination of levels of the main constituents in e-liquids by near infrared spectroscopy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439909/
https://www.ncbi.nlm.nih.gov/pubmed/37598198
http://dx.doi.org/10.1038/s41598-023-40422-z
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