Cargando…
A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid
Carbon dioxide (CO(2)) is a greenhouse gas in the atmosphere and scientists are working on converting it to useful products, thereby reducing its quantity in the atmosphere. For converting CO(2), different approaches are used, and among them, electrochemistry is found to be the most common and more...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780487/ https://www.ncbi.nlm.nih.gov/pubmed/35062579 http://dx.doi.org/10.3390/s22020618 |
_version_ | 1784637850879262720 |
---|---|
author | Sha, Mizaj Shabil Maurya, Muni Raj Geetha, Mithra Kumar, Bijandra Abdullah, Aboubakr M. Sadasivuni, Kishor Kumar |
author_facet | Sha, Mizaj Shabil Maurya, Muni Raj Geetha, Mithra Kumar, Bijandra Abdullah, Aboubakr M. Sadasivuni, Kishor Kumar |
author_sort | Sha, Mizaj Shabil |
collection | PubMed |
description | Carbon dioxide (CO(2)) is a greenhouse gas in the atmosphere and scientists are working on converting it to useful products, thereby reducing its quantity in the atmosphere. For converting CO(2), different approaches are used, and among them, electrochemistry is found to be the most common and more efficient technique. Current methods for detecting the products of electrochemical CO(2) conversion are time-consuming and complex. To combat this, a simple, cost-effective colorimetric method has been developed to detect methanol, ethanol, and formic acid, which are formed electrochemically from CO(2). In the present work, the highly efficient sensitive dyes were successfully established to detect these three compounds under optimized conditions. These dyes demonstrated excellent selectivity and showed no cross-reaction with other products generated in the CO(2) conversion system. In the analysis using these three compounds, this strategy shows good specificity and limit of detection (LOD, ~0.03–0.06 ppm). A cost-effective and sensitive Internet of Things (IoT) colorimetric sensor prototype was developed to implement these dyes systems for practical and real-time application. Employing the dyes as sensing elements, the prototype exhibits unique red, green, and blue (RGB) values upon exposure to test solutions with a short response time of 2 s. Detection of these compounds via this new approach has been proven effective by comparing them with nuclear magnetic resonance (NMR). This novel approach can replace heavy-duty instruments such as high-pressure liquid chromatography (HPLC), gas chromatography (G.C.), and NMR due to its extraordinary selectivity and rapidity. |
format | Online Article Text |
id | pubmed-8780487 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87804872022-01-22 A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid Sha, Mizaj Shabil Maurya, Muni Raj Geetha, Mithra Kumar, Bijandra Abdullah, Aboubakr M. Sadasivuni, Kishor Kumar Sensors (Basel) Article Carbon dioxide (CO(2)) is a greenhouse gas in the atmosphere and scientists are working on converting it to useful products, thereby reducing its quantity in the atmosphere. For converting CO(2), different approaches are used, and among them, electrochemistry is found to be the most common and more efficient technique. Current methods for detecting the products of electrochemical CO(2) conversion are time-consuming and complex. To combat this, a simple, cost-effective colorimetric method has been developed to detect methanol, ethanol, and formic acid, which are formed electrochemically from CO(2). In the present work, the highly efficient sensitive dyes were successfully established to detect these three compounds under optimized conditions. These dyes demonstrated excellent selectivity and showed no cross-reaction with other products generated in the CO(2) conversion system. In the analysis using these three compounds, this strategy shows good specificity and limit of detection (LOD, ~0.03–0.06 ppm). A cost-effective and sensitive Internet of Things (IoT) colorimetric sensor prototype was developed to implement these dyes systems for practical and real-time application. Employing the dyes as sensing elements, the prototype exhibits unique red, green, and blue (RGB) values upon exposure to test solutions with a short response time of 2 s. Detection of these compounds via this new approach has been proven effective by comparing them with nuclear magnetic resonance (NMR). This novel approach can replace heavy-duty instruments such as high-pressure liquid chromatography (HPLC), gas chromatography (G.C.), and NMR due to its extraordinary selectivity and rapidity. MDPI 2022-01-13 /pmc/articles/PMC8780487/ /pubmed/35062579 http://dx.doi.org/10.3390/s22020618 Text en © 2022 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 Sha, Mizaj Shabil Maurya, Muni Raj Geetha, Mithra Kumar, Bijandra Abdullah, Aboubakr M. Sadasivuni, Kishor Kumar A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid |
title | A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid |
title_full | A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid |
title_fullStr | A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid |
title_full_unstemmed | A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid |
title_short | A Smart Colorimetric Platform for Detection of Methanol, Ethanol and Formic Acid |
title_sort | smart colorimetric platform for detection of methanol, ethanol and formic acid |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780487/ https://www.ncbi.nlm.nih.gov/pubmed/35062579 http://dx.doi.org/10.3390/s22020618 |
work_keys_str_mv | AT shamizajshabil asmartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT mauryamuniraj asmartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT geethamithra asmartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT kumarbijandra asmartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT abdullahaboubakrm asmartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT sadasivunikishorkumar asmartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT shamizajshabil smartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT mauryamuniraj smartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT geethamithra smartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT kumarbijandra smartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT abdullahaboubakrm smartcolorimetricplatformfordetectionofmethanolethanolandformicacid AT sadasivunikishorkumar smartcolorimetricplatformfordetectionofmethanolethanolandformicacid |