Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/121095
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Type: Journal article
Title: Facile synthesis of ternary graphene nanocomposites with doped metal oxide and conductive polymers as electrode materials for high performance supercapacitors
Author: Ishaq, S.
Moussa, M.
Kanwal, F.
Ehsan, M.
Saleem, M.
Van, T.N.
Losic, D.
Citation: Scientific Reports, 2019; 9(1):5974-1-5974-11
Publisher: Nature Publishing Group
Issue Date: 2019
ISSN: 2045-2322
2045-2322
Statement of
Responsibility: 
Saira Ishaq, Mahmoud Moussa, Farah Kanwal, Muhammad Ehsan, Muhammad Saleem, Truc Ngo Van and Dusan Losic
Abstract: Supercapacitors (SCs) due to their high energy density, fast charge storage and energy transfer, long charge discharge curves and low costs are very attractive for designing new generation of energy storage devices. In this work we present a simple and scalable synthetic approach to engineer ternary composite as electrode material based on combination of graphene with doped metal oxides (iron oxide) and conductive polymer (polypyrrole) with aims to achieve supercapacitors with very high gravimetric and areal capacitances. In the first step a binary composite with graphene mixed with doped iron oxide (rGO/MeFe2O4) (Me = Mn, Ni) was synthesized using new single step process with NaOH acting as a coprecipitation and GO reducing agent. This rGO/MnFe2O4 composite electrode showed gravimetric capacitance of 147 Fg-1 and areal capacitance of 232 mFcm-2 at scan rate of 5 mVs-1. In the final step a conductive polypyrrole was included to prepare a ternary composite graphene/metal doped iron oxide/polypyrrole (rGO/MnFe2O4/Ppy) electrode. Ternary composite electrode showed significantly improved gravimetric capacitance and areal capacitance of 232 Fg-1 and 395 mFcm-2 respectively indicating synergistic impact of Ppy additives. The method is promising to fabricate advanced electrode materials for high performing supercapacitors combining graphene, doped iron oxide and conductive polymers.
Rights: © The Author(s) 2019. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
RMID: 0030113237
DOI: 10.1038/s41598-019-41939-y
Grant ID: http://purl.org/au-research/grants/arc/IH150100003
Appears in Collections:Computer Science publications

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