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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Differential Capacitance and Energetics of the Electrical Double Layer of Graphene Oxide Supercapacitors: Impact of the Oxidation Degree

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Author(s):
Paulista Neto, Antenor J. [1] ; Fileti, Eudes Eterno [2]
Total Authors: 2
Affiliation:
[1] Univ Fed ABC, Ctr Ciencias Nat & Humanas, BR-09210170 Santo Andre, SP - Brazil
[2] Univ Fed Sao Paulo, Inst Ciencia & Tecnol, BR-12247014 Sao Jose Dos Campos, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: Journal of Physical Chemistry C; v. 122, n. 38, p. 21824-21832, SEP 27 2018.
Web of Science Citations: 8
Abstract

Graphene oxide (GO)-based materials have been considered for potential energy storage applications, in particular supercapacitors. Here, for the first time, we present a detailed analysis of the properties of GO-based supercapacitors as a function of both chemical composition and charge density on the electrodes. Differential capacitance was determined and the effect of the degree of oxidation of the electrodes was taken into account. Also, structural and energetic details on the electrode-electrolyte interaction and, consequently, the double-layer electric structure were analyzed. The differential capacitance value for all supercapacitors is within the range of 1.5-5.4 mu F cm(-2) in the +/- 3 V window for the electrode potential and presents the highest value for the R20 system, which also had the highest mean integral capacitance. One important result is the gradual transition from bell-shaped to camel-shaped as the degree of oxidation increases. The results presented here provide the missing complement for a detailed and complete description of the properties of GO supercapacitors, indicating how they behave with the variation of charge density and degree of oxidation. (AU)

FAPESP's process: 17/11631-2 - CINE: computational materials design based on atomistic simulations, meso-scale, multi-physics, and artificial intelligence for energy applications
Grantee:Juarez Lopes Ferreira da Silva
Support Opportunities: Research Grants - Research Centers in Engineering Program