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Graphene-based nanocomposites for energy storage and conversion in lithium batteries, supercapacitors and fuel cells

Open access
Mahmood, Nasir, Zhang, Chenzhen, Yin, Han, Hou, Yanglong·2014·J. Mater. Chem. A

Abstract

Due to their unique properties, together with their ease of synthesis and functionalization, graphene-based materials have been showing great potential in energy storage and conversion. These hybrid structures display excellent material characteristics, including high carrier mobility, faster recombination rate and long-time stability. In this review, after a short introduction to graphene and its derivatives, we summarize the recent advances in the synthesis and applications of graphene and its derivatives in the fields of energy storage (lithium ion, lithium–air, lithium–sulphur batteries and supercapacitors) and conversion (oxygen reduction reaction for fuel cells). This article further highlights the working principles and problems hindering the practical applications of graphene-based materials in lithium batteries, supercapacitors and fuel cells. Future research trends towards new methodologies to the design and the synthesis of graphene-based nanocomposite with unique architectures for electrochemical energy storage and conversion are also proposed.

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Crossref · 10.1039/c3ta13033a

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Metadata

Authors
Mahmood, N., Zhang, C., Yin, H., & Hou, Y.
Venue
J. Mater. Chem. A
Published
2014
Volume
2
Issue
1
Pages
15-32
ISSN
  • 2050-7488 (ISSN-L)
  • 2050-7496
OpenAlex
W2136923822
Cited by
502
References
1
FWCI
18.01
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Graphene-based nanocomposites for energy storage and conversion in lithium batteries, supercapacitors and fuel cells. https://app.cochat.ai/papers/10.1039/c3ta13033a
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Mahmood, N., Zhang, C., Yin, H., & Hou, Y. (2014). Graphene-based nanocomposites for energy storage and conversion in lithium batteries, supercapacitors and fuel cells. J. Mater. Chem. A. https://doi.org/10.1039/c3ta13033a

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.