relation: https://khub.utp.edu.my/scholars/18970/
title: Modeling and Simulation of Graphene-based Working Electrodes for Highly Capacitive Energy Storage Devices
creator: Rahman, M.O.
creator: Nor, N.B.M.
creator: Kannan, R.
creator: Shukur, M.F.B.A.
creator: Hasan, M.M.
creator: Mostafa, M.G.
description: The significance of supercapacitors in the energy sector is growing rapidly owing to their exceptional properties such as high specific power and long cycle of life. This paper presents the design and model of a working electrode for supercapacitors and examined the electrochemical performance of the model developed for 2-D cyclic voltammetry (CV) using COMSOL Multiphysics electro analysis application. The electrode is designed to show maximum current density for an applied potential across it from where capacitive performance can be predicted. The simulation of working electrodes is carried out for CVs by sweeping the scan rates for different geometries of electrodes and the plots exhibit multiple graphs for CV, electrode potential for charge-discharge (CD), and surface concentration profile. The findings demonstrate that the highest peak currents of 0.08A, and 0.45A are visible in the plot for circular and squire-shaped geometries, respectively due to the highest scan rate of 100 mV/s in the applied potential range of -0.7V to 0.5V. On the other hand, a lower scan rate (5mV/s) shows the smallest peak currents of 0.02A and 0.01A for circular and squire-shaped geometries, respectively. © 2023 IEEE.
date: 2023
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Rahman, M.O. and Nor, N.B.M. and Kannan, R. and Shukur, M.F.B.A. and Hasan, M.M. and Mostafa, M.G.  (2023) Modeling and Simulation of Graphene-based Working Electrodes for Highly Capacitive Energy Storage Devices.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182952295&doi=10.1109%2fIEACon57683.2023.10370346&partnerID=40&md5=67dfc598bcd33273a91c96335f16f452
relation: 10.1109/IEACon57683.2023.10370346
identifier: 10.1109/IEACon57683.2023.10370346