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Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks
Air pollution is becoming an increasingly important global issue. Toxic gases such as ammonia, nitrogen dioxide, and volatile organic compounds (VOCs) like phenol are very common air pollutants. To date, various sensing methods have been proposed to detect these toxic gases. Researchers are trying t...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8152072/ https://www.ncbi.nlm.nih.gov/pubmed/34067948 http://dx.doi.org/10.3390/s21103386 |
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author | Dong, Qichao Xiao, Min Chu, Zengyong Li, Guochen Zhang, Ye |
author_facet | Dong, Qichao Xiao, Min Chu, Zengyong Li, Guochen Zhang, Ye |
author_sort | Dong, Qichao |
collection | PubMed |
description | Air pollution is becoming an increasingly important global issue. Toxic gases such as ammonia, nitrogen dioxide, and volatile organic compounds (VOCs) like phenol are very common air pollutants. To date, various sensing methods have been proposed to detect these toxic gases. Researchers are trying their best to build sensors with the lowest detection limit, the highest sensitivity, and the best selectivity. As a 2D material, graphene is very sensitive to many gases and so can be used for gas sensors. Recent studies have shown that graphene with a 3D structure can increase the gas sensitivity of the sensors. The limit of detection (LOD) of the sensors can be upgraded from ppm level to several ppb level. In this review, the recent progress of the gas sensors based on 3D graphene frameworks in the detection of harmful gases is summarized and discussed. |
format | Online Article Text |
id | pubmed-8152072 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-81520722021-05-27 Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks Dong, Qichao Xiao, Min Chu, Zengyong Li, Guochen Zhang, Ye Sensors (Basel) Review Air pollution is becoming an increasingly important global issue. Toxic gases such as ammonia, nitrogen dioxide, and volatile organic compounds (VOCs) like phenol are very common air pollutants. To date, various sensing methods have been proposed to detect these toxic gases. Researchers are trying their best to build sensors with the lowest detection limit, the highest sensitivity, and the best selectivity. As a 2D material, graphene is very sensitive to many gases and so can be used for gas sensors. Recent studies have shown that graphene with a 3D structure can increase the gas sensitivity of the sensors. The limit of detection (LOD) of the sensors can be upgraded from ppm level to several ppb level. In this review, the recent progress of the gas sensors based on 3D graphene frameworks in the detection of harmful gases is summarized and discussed. MDPI 2021-05-13 /pmc/articles/PMC8152072/ /pubmed/34067948 http://dx.doi.org/10.3390/s21103386 Text en © 2021 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 | Review Dong, Qichao Xiao, Min Chu, Zengyong Li, Guochen Zhang, Ye Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks |
title | Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks |
title_full | Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks |
title_fullStr | Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks |
title_full_unstemmed | Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks |
title_short | Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks |
title_sort | recent progress of toxic gas sensors based on 3d graphene frameworks |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8152072/ https://www.ncbi.nlm.nih.gov/pubmed/34067948 http://dx.doi.org/10.3390/s21103386 |
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