Analytical modeling of glucose biosensors based on carbon nanotubes

In recent years, carbon nanotubes have received widespread attention as promising carbonbased nanoelectronic devices. Due to their exceptional physical, chemical, and electrical properties, namely a high surface-to-volume ratio, their enhanced electron transfer properties, and their high thermal con...

Full description

Saved in:
Bibliographic Details
Main Authors: Pourasl, Ali H., Ahmadi, Mohammad Taghi, Rahmani, Meisam, Chin, Huei Chaeng, Lim, Cheng Siong, Ismail, Razali, Tan, Michael Loong Peng
Format: Article
Language:English
Published: Springer Open 2014
Subjects:
Online Access:http://eprints.utm.my/id/eprint/51853/1/RazaliIsmail2014_AnalyticalModelingOfGlucoseBiosensors.pdf
http://eprints.utm.my/id/eprint/51853/
http://dx.doi.org/10.1186/1556-276X-9-33
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utm.51853
record_format eprints
spelling my.utm.518532018-08-27T03:41:24Z http://eprints.utm.my/id/eprint/51853/ Analytical modeling of glucose biosensors based on carbon nanotubes Pourasl, Ali H. Ahmadi, Mohammad Taghi Rahmani, Meisam Chin, Huei Chaeng Lim, Cheng Siong Ismail, Razali Tan, Michael Loong Peng TK Electrical engineering. Electronics Nuclear engineering In recent years, carbon nanotubes have received widespread attention as promising carbonbased nanoelectronic devices. Due to their exceptional physical, chemical, and electrical properties, namely a high surface-to-volume ratio, their enhanced electron transfer properties, and their high thermal conductivity, carbon nanotubes can be used effectively as electrochemical sensors. The integration of carbon nanotubes with a functional group provides a good and solid support for the immobilization of enzymes. The determination of glucose levels using biosensors, particularly in the medical diagnostics and food industries, is gaining mass appeal. Glucose biosensors detect the glucose molecule by catalyzing glucose to gluconic acid and H2O2 in the presence of oxygen. This action provides high accuracy and a quick detection rate. In this paper, a single-wall carbon nanotube field-effect transistor biosensor for glucose detection is analytically modeled. In the proposed model, the glucose concentration is presented as a function of gate voltage. Subsequently, the proposed model is compared with existing experimental data. A good consensus between the model and the experimental data is reported. The simulated data demonstrate that the analytical model can be employed with an electrochemical glucose sensor to predict the behavior of the sensing mechanism in biosensors. Springer Open 2014 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/51853/1/RazaliIsmail2014_AnalyticalModelingOfGlucoseBiosensors.pdf Pourasl, Ali H. and Ahmadi, Mohammad Taghi and Rahmani, Meisam and Chin, Huei Chaeng and Lim, Cheng Siong and Ismail, Razali and Tan, Michael Loong Peng (2014) Analytical modeling of glucose biosensors based on carbon nanotubes. Nanoscale Research Letters, 9 . ISSN 1556-276X http://dx.doi.org/10.1186/1556-276X-9-33 DOI: 10.1186/1556-276X-9-33
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Pourasl, Ali H.
Ahmadi, Mohammad Taghi
Rahmani, Meisam
Chin, Huei Chaeng
Lim, Cheng Siong
Ismail, Razali
Tan, Michael Loong Peng
Analytical modeling of glucose biosensors based on carbon nanotubes
description In recent years, carbon nanotubes have received widespread attention as promising carbonbased nanoelectronic devices. Due to their exceptional physical, chemical, and electrical properties, namely a high surface-to-volume ratio, their enhanced electron transfer properties, and their high thermal conductivity, carbon nanotubes can be used effectively as electrochemical sensors. The integration of carbon nanotubes with a functional group provides a good and solid support for the immobilization of enzymes. The determination of glucose levels using biosensors, particularly in the medical diagnostics and food industries, is gaining mass appeal. Glucose biosensors detect the glucose molecule by catalyzing glucose to gluconic acid and H2O2 in the presence of oxygen. This action provides high accuracy and a quick detection rate. In this paper, a single-wall carbon nanotube field-effect transistor biosensor for glucose detection is analytically modeled. In the proposed model, the glucose concentration is presented as a function of gate voltage. Subsequently, the proposed model is compared with existing experimental data. A good consensus between the model and the experimental data is reported. The simulated data demonstrate that the analytical model can be employed with an electrochemical glucose sensor to predict the behavior of the sensing mechanism in biosensors.
format Article
author Pourasl, Ali H.
Ahmadi, Mohammad Taghi
Rahmani, Meisam
Chin, Huei Chaeng
Lim, Cheng Siong
Ismail, Razali
Tan, Michael Loong Peng
author_facet Pourasl, Ali H.
Ahmadi, Mohammad Taghi
Rahmani, Meisam
Chin, Huei Chaeng
Lim, Cheng Siong
Ismail, Razali
Tan, Michael Loong Peng
author_sort Pourasl, Ali H.
title Analytical modeling of glucose biosensors based on carbon nanotubes
title_short Analytical modeling of glucose biosensors based on carbon nanotubes
title_full Analytical modeling of glucose biosensors based on carbon nanotubes
title_fullStr Analytical modeling of glucose biosensors based on carbon nanotubes
title_full_unstemmed Analytical modeling of glucose biosensors based on carbon nanotubes
title_sort analytical modeling of glucose biosensors based on carbon nanotubes
publisher Springer Open
publishDate 2014
url http://eprints.utm.my/id/eprint/51853/1/RazaliIsmail2014_AnalyticalModelingOfGlucoseBiosensors.pdf
http://eprints.utm.my/id/eprint/51853/
http://dx.doi.org/10.1186/1556-276X-9-33
_version_ 1643653081074761728
score 13.209306