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A carrier velocity model for electrical detection of gas molecules
Nanomaterial-based sensors with high sensitivity, fast response and recovery time, large detection range, and high chemical stability are in immense demand for the detection of hazardous gas molecules. Graphene nanoribbons (GNRs) which have exceptional electrical, physical, and chemical properties c...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Beilstein-Institut
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423604/ https://www.ncbi.nlm.nih.gov/pubmed/30931206 http://dx.doi.org/10.3762/bjnano.10.64 |
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author | Hosseingholi Pourasl, Ali Ariffin, Sharifah Hafizah Syed Ahmadi, Mohammad Taghi Ismail, Razali Gharaei, Niayesh |
author_facet | Hosseingholi Pourasl, Ali Ariffin, Sharifah Hafizah Syed Ahmadi, Mohammad Taghi Ismail, Razali Gharaei, Niayesh |
author_sort | Hosseingholi Pourasl, Ali |
collection | PubMed |
description | Nanomaterial-based sensors with high sensitivity, fast response and recovery time, large detection range, and high chemical stability are in immense demand for the detection of hazardous gas molecules. Graphene nanoribbons (GNRs) which have exceptional electrical, physical, and chemical properties can fulfil all of these requirements. The detection of gas molecules using gas sensors, particularly in medical diagnostics and safety applications, is receiving particularly high demand. GNRs exhibit remarkable changes in their electrical characteristics when exposed to different gases through molecular adsorption. In this paper, the adsorption effects of the target gas molecules (CO and NO) on the electrical properties of the armchair graphene nanoribbon (AGNR)-based sensor are analytically modelled. Thus, the energy dispersion relation of AGNR is developed considering the molecular adsorption effect using a tight binding (TB) method. The carrier velocity is calculated based on the density of states (DOS) and carrier concentration (n) to obtain I–V characteristics and to monitor its variation in the presence of the gas molecules. Furthermore, the I–V characteristics and energy band structure of the AGNR sensor are simulated using first principle calculations to investigate the gas adsorption effects on these properties. To ensure the accuracy of the proposed model, the I–V characteristics of the AGNR sensor that are simulated based both on the proposed model and first principles calculations are compared, and an acceptable agreement is achieved. |
format | Online Article Text |
id | pubmed-6423604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Beilstein-Institut |
record_format | MEDLINE/PubMed |
spelling | pubmed-64236042019-03-29 A carrier velocity model for electrical detection of gas molecules Hosseingholi Pourasl, Ali Ariffin, Sharifah Hafizah Syed Ahmadi, Mohammad Taghi Ismail, Razali Gharaei, Niayesh Beilstein J Nanotechnol Full Research Paper Nanomaterial-based sensors with high sensitivity, fast response and recovery time, large detection range, and high chemical stability are in immense demand for the detection of hazardous gas molecules. Graphene nanoribbons (GNRs) which have exceptional electrical, physical, and chemical properties can fulfil all of these requirements. The detection of gas molecules using gas sensors, particularly in medical diagnostics and safety applications, is receiving particularly high demand. GNRs exhibit remarkable changes in their electrical characteristics when exposed to different gases through molecular adsorption. In this paper, the adsorption effects of the target gas molecules (CO and NO) on the electrical properties of the armchair graphene nanoribbon (AGNR)-based sensor are analytically modelled. Thus, the energy dispersion relation of AGNR is developed considering the molecular adsorption effect using a tight binding (TB) method. The carrier velocity is calculated based on the density of states (DOS) and carrier concentration (n) to obtain I–V characteristics and to monitor its variation in the presence of the gas molecules. Furthermore, the I–V characteristics and energy band structure of the AGNR sensor are simulated using first principle calculations to investigate the gas adsorption effects on these properties. To ensure the accuracy of the proposed model, the I–V characteristics of the AGNR sensor that are simulated based both on the proposed model and first principles calculations are compared, and an acceptable agreement is achieved. Beilstein-Institut 2019-03-04 /pmc/articles/PMC6423604/ /pubmed/30931206 http://dx.doi.org/10.3762/bjnano.10.64 Text en Copyright © 2019, Hosseingholi Pourasl et al. https://creativecommons.org/licenses/by/4.0https://www.beilstein-journals.org/bjnano/termsThis is an Open Access article under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0). Please note that the reuse, redistribution and reproduction in particular requires that the authors and source are credited. The license is subject to the Beilstein Journal of Nanotechnology terms and conditions: (https://www.beilstein-journals.org/bjnano/terms) |
spellingShingle | Full Research Paper Hosseingholi Pourasl, Ali Ariffin, Sharifah Hafizah Syed Ahmadi, Mohammad Taghi Ismail, Razali Gharaei, Niayesh A carrier velocity model for electrical detection of gas molecules |
title | A carrier velocity model for electrical detection of gas molecules |
title_full | A carrier velocity model for electrical detection of gas molecules |
title_fullStr | A carrier velocity model for electrical detection of gas molecules |
title_full_unstemmed | A carrier velocity model for electrical detection of gas molecules |
title_short | A carrier velocity model for electrical detection of gas molecules |
title_sort | carrier velocity model for electrical detection of gas molecules |
topic | Full Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6423604/ https://www.ncbi.nlm.nih.gov/pubmed/30931206 http://dx.doi.org/10.3762/bjnano.10.64 |
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