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Hydrogen Sulfide Gas Detection via Multivariate Optical Computing
Hydrogen-sulfide gas is a toxic, colorless gas with a pungent odor that occurs naturally as a decomposition by-product. It is critical to monitor the concentration of hydrogen sulfide. Multivariate optical computing (MOC) is a method that can monitor analytes while minimizing responses to interferen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069242/ https://www.ncbi.nlm.nih.gov/pubmed/29932144 http://dx.doi.org/10.3390/s18072006 |
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author | Dai, Bin Jones, Christopher Michael Pearl, Megan Pelletier, Mickey Myrick, Mickey |
author_facet | Dai, Bin Jones, Christopher Michael Pearl, Megan Pelletier, Mickey Myrick, Mickey |
author_sort | Dai, Bin |
collection | PubMed |
description | Hydrogen-sulfide gas is a toxic, colorless gas with a pungent odor that occurs naturally as a decomposition by-product. It is critical to monitor the concentration of hydrogen sulfide. Multivariate optical computing (MOC) is a method that can monitor analytes while minimizing responses to interferences. MOC is a technique by which an analogue calculation is performed entirely in the optical domain, which simplifies instrument design, prevents the drift of a calibration, and increases the strength and durability of spectroscopic instrumentation against physical perturbation when used for chemical detection and identification. This paper discusses the detection of hydrogen-sulfide gas in the ultraviolet (UV) spectral region in the presence of interfering gaseous species. A laboratory spectroscopic measurement system was set up to acquire the UV spectra of H(2)S and interference gas mixtures in high-pressure/high-temperature (HPHT) conditions. These spectra were used to guide the design and fabrication of a multivariate optical element (MOE), which has an expected measurement relative accuracy of 3.3% for H(2)S, with a concentration in the range of 0–150 nmol/mL. An MOC validation system with the MOE was used to test three samples of H(2)S and mercaptans mixtures under various pressures, and the relative accuracy of H(2)S measurement was determined to be 8.05%. |
format | Online Article Text |
id | pubmed-6069242 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-60692422018-08-07 Hydrogen Sulfide Gas Detection via Multivariate Optical Computing Dai, Bin Jones, Christopher Michael Pearl, Megan Pelletier, Mickey Myrick, Mickey Sensors (Basel) Article Hydrogen-sulfide gas is a toxic, colorless gas with a pungent odor that occurs naturally as a decomposition by-product. It is critical to monitor the concentration of hydrogen sulfide. Multivariate optical computing (MOC) is a method that can monitor analytes while minimizing responses to interferences. MOC is a technique by which an analogue calculation is performed entirely in the optical domain, which simplifies instrument design, prevents the drift of a calibration, and increases the strength and durability of spectroscopic instrumentation against physical perturbation when used for chemical detection and identification. This paper discusses the detection of hydrogen-sulfide gas in the ultraviolet (UV) spectral region in the presence of interfering gaseous species. A laboratory spectroscopic measurement system was set up to acquire the UV spectra of H(2)S and interference gas mixtures in high-pressure/high-temperature (HPHT) conditions. These spectra were used to guide the design and fabrication of a multivariate optical element (MOE), which has an expected measurement relative accuracy of 3.3% for H(2)S, with a concentration in the range of 0–150 nmol/mL. An MOC validation system with the MOE was used to test three samples of H(2)S and mercaptans mixtures under various pressures, and the relative accuracy of H(2)S measurement was determined to be 8.05%. MDPI 2018-06-22 /pmc/articles/PMC6069242/ /pubmed/29932144 http://dx.doi.org/10.3390/s18072006 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Dai, Bin Jones, Christopher Michael Pearl, Megan Pelletier, Mickey Myrick, Mickey Hydrogen Sulfide Gas Detection via Multivariate Optical Computing |
title | Hydrogen Sulfide Gas Detection via Multivariate Optical Computing |
title_full | Hydrogen Sulfide Gas Detection via Multivariate Optical Computing |
title_fullStr | Hydrogen Sulfide Gas Detection via Multivariate Optical Computing |
title_full_unstemmed | Hydrogen Sulfide Gas Detection via Multivariate Optical Computing |
title_short | Hydrogen Sulfide Gas Detection via Multivariate Optical Computing |
title_sort | hydrogen sulfide gas detection via multivariate optical computing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069242/ https://www.ncbi.nlm.nih.gov/pubmed/29932144 http://dx.doi.org/10.3390/s18072006 |
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