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Surface Study of Volatile Organic Compounds (VOCs) Biomarkers Adsorption on Functionalized Graphene and its Application in FET Based Biosensors


Surface Study of Volatile Organic Compounds (VOCs) Biomarkers Adsorption on Functionalized Graphene and its Application in FET Based Biosensors

Singh, Paramjot ORCID: https://orcid.org/0000-0003-3830-9583 (2021) Surface Study of Volatile Organic Compounds (VOCs) Biomarkers Adsorption on Functionalized Graphene and its Application in FET Based Biosensors. Masters thesis, Concordia University.

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In this work, we have designed and simulated a graphene field-effect transistor, GFET, with the purpose of developing a sensitive biosensor for methanethiol, a biomarker for bacterial infections and ethyl butyrate, a biomarker for COVID-19.
The surface of a graphene layer is engineered by manipulation of its surface structure and best cases are used as the channel of the GFET. Three methods, doping the crystal structure of graphene, decorating the surface with transition metals like Platinum and Palladium and defected graphene nanoribbons are utilized to induce the bandgap in the graphene layers.
The techniques also change the surface chemistry of the graphene by enhancing its adsorption characteristics and make binding between graphene and biomarker possible. All the physical parameters are calculated for various variants of graphene in the absence and presence of the biomarker using counterpoise energy corrected density functional theory in Quantum ATK. The device was modelled using the finite element method in COMSOL Multiphysics. Our studies show that the sensitivity of the device is affected by the structural parameters of the device, the electrical properties of the graphene, and with adsorption of the biomarkers. It was found that the devices made of graphene layers decorated with transition metals show higher sensitivities toward detecting the biomarkers compared with those made by doped graphene layers and nanoribbons.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Thesis (Masters)
Authors:Singh, Paramjot
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Electrical and Computer Engineering
Date:22 December 2021
Thesis Supervisor(s):Kahrizi, Mojtaba
Keywords:Graphene; Biosensor; DFT; COMSOL; FET; COVID-19
ID Code:990135
Deposited By: Paramjot Singh
Deposited On:16 Jun 2022 15:13
Last Modified:16 Jun 2022 15:13


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