Keyword search (4,163 papers available)

"Sensors (Basel)" Category Publications:

Title Authors PubMed ID
1 On the Impact of Biceps Muscle Fatigue in Human Activity Recognition. Elshafei M, Costa DE, Shihab E 33557239
ENCS
2 Towards Detecting Biceps Muscle Fatigue in Gym Activity Using Wearables. Elshafei M, Shihab E 33498702
ENCS
3 Finite Element Modelling of Bandgap Engineered Graphene FET with the Application in Sensing Methanethiol Biomarker. Singh P, Abedini Sohi P, Kahrizi M 33467459
ENCS
4 A Benchmark of Data Stream Classification for Human Activity Recognition on Connected Objects. Khannouz M; Glatard T; 33202905
ENCS
5 Contactless Capacitive Electrocardiography Using Hybrid Flexible Printed Electrodes. Lessard-Tremblay M, Weeks J, Morelli L, Cowan G, Gagnon G, Zednik RJ 32927651
ENCS
6 Determining the Optimal Restricted Driving Zone Using Genetic Algorithm in a Smart City. Azami P, Jan T, Iranmanesh S, Ameri Sianaki O, Hajiebrahimi S 32316356
ENCS
7 A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors. Dehghani A, Sarbishei O, Glatard T, Shihab E 31752158
ENCS
8 Characterization and Efficient Management of Big Data in IoT-Driven Smart City Development. Alsaig A, Alagar V, Chammaa Z, Shiri N 31141899
CONCORDIA
9 A Crowdsensing Based Analytical Framework for Perceptional Degradation of OTT Web Browsing. Li K, Wang H, Xu X, Du Y, Liu Y, Ahmad MO 29762493
ENCS
10 Fast Feature-Preserving Approach to Carpal Bone Surface Denoising. Salim I, Hamza AB 30037109
ENCS
11 Big Data-Driven Cellular Information Detection and Coverage Identification. Wang H, Xie S, Li K, Ahmad MO 30813353
ENCS
12 Surface Profiling and Core Evaluation of Aluminum Honeycomb Sandwich Aircraft Panels Using Multi-Frequency Eddy Current Testing. Reyno T, Underhill PR, Krause TW, Marsden C, Wowk D 28906434
PHYSICS

 

Title:Finite Element Modelling of Bandgap Engineered Graphene FET with the Application in Sensing Methanethiol Biomarker.
Authors:Singh PAbedini Sohi PKahrizi M
Link:https://www.ncbi.nlm.nih.gov/pubmed/33467459
DOI:10.3390/s21020580
Publication:Sensors (Basel, Switzerland)
Keywords:COMSOL modellingDFTGFETbandgap engineeringfunctionalized graphenemethanethiol biosensor
PMID:33467459 Category:Sensors (Basel) Date Added:2021-01-21
Dept Affiliation: ENCS
1 Department of Electrical and Computer Engineering, Concordia University, Montreal, QC H3G1M8, Canada.

Description:

Finite Element Modelling of Bandgap Engineered Graphene FET with the Application in Sensing Methanethiol Biomarker.

Sensors (Basel). 2021 Jan 15; 21(2):

Authors: Singh P, Abedini Sohi P, Kahrizi M

Abstract

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. The surface of a graphene layer is functionalized by manipulation of its surface structure and is used as the channel of the GFET. Two methods, doping the crystal structure of graphene and decorating the surface by transition metals (TMs), are utilized to change the electrical properties of the graphene layers to make them suitable as a channel of the GFET. The techniques also change the surface chemistry of the graphene, enhancing its adsorption characteristics and making 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 (DFT). The device was modelled using COMSOL Multiphysics. Our studies show that the sensitivity of the device is affected by structural parameters of the device, the electrical properties of the graphene, and with adsorption of the biomarker. It was found that the devices made of graphene layers decorated with TM show higher sensitivities toward detecting the biomarker compared with those made by doped graphene layers.

PMID: 33467459 [PubMed - in process]





BookR developed by Sriram Narayanan
for the Concordia University School of Health
Copyright © 2011-2026
Cookie settings
Concordia University