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Bilayer graphene application on NO2 sensor modelling

Akbari, Elnaz and Yusof, Rubiyah and Ahmadi, Mohammad Taghi and Enzevaee, Aria and Kiani, Mohammad Javad and Karimi, Hediyeh and Rahmani, Meisam (2014) Bilayer graphene application on NO2 sensor modelling. Journal of Nanomaterials . ISSN 1687-4110

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Official URL: http://dx.doi.org/10.1155/2014/534105

Abstract

Graphene is one of the carbon allotropes which is a single atom thin layer with sp2 hybridized and two-dimensional (2D) honeycomb structure of carbon. As an outstanding material exhibiting unique mechanical, electrical, and chemical characteristics including high strength, high conductivity, and high surface area, graphene has earned a remarkable position in today's experimental and theoretical studies as well as industrial applications. One such application incorporates the idea of using graphene to achieve accuracy and higher speed in detection devices utilized in cases where gas sensing is required. Although there are plenty of experimental studies in this field, the lack of analytical models is felt deeply. To start with modelling, the field effect transistor- (FET-) based structure has been chosen to serve as the platform and bilayer graphene density of state variation effect by N O 2 injection has been discussed. The chemical reaction between graphene and gas creates new carriers in graphene which cause density changes and eventually cause changes in the carrier velocity. In the presence of N O 2 gas, electrons are donated to the FET channel which is employed as a sensing mechanism. In order to evaluate the accuracy of the proposed models, the results obtained are compared with the existing experimental data and acceptable agreement is reported.

Item Type:Article
Uncontrolled Keywords:field effect transistors, graphene, honeycomb structures
Subjects:T Technology > TP Chemical technology
Divisions:Malaysia-Japan International Institute of Technology
ID Code:51991
Deposited By: Siti Nor Hashidah Zakaria
Deposited On:01 Feb 2016 03:53
Last Modified:30 Nov 2018 06:57

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