title: Analytical modeling of glucose biosensors based on carbon nanotubes.
abstract: In recent years, carbon nanotubes have received widespread attention as promising carbon-based 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 hydrogen peroxide 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.
authors.forename: Ali H
authors.initials: AH
authors.lastname: Pourasl
authors.forename: Mohammad Taghi
authors.initials: MT
authors.lastname: Ahmadi
authors.forename: Meisam
authors.initials: M
authors.lastname: Rahmani
authors.forename: Huei Chaeng
authors.initials: HC
authors.lastname: Chin
authors.forename: Cheng Siong
authors.initials: CS
authors.lastname: Lim
authors.forename: Razali
authors.initials: R
authors.lastname: Ismail
authors.affiliation: Faculty of Electrical Engineering, Universiti Teknologi Malaysia UTM, Skudai, Johor 81310, Malaysia. michael@fke.utm.my.
authors.forename: Michael Loong Peng
authors.initials: ML
authors.lastname: Tan