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Cited by 686

The DOI matches its Crossref record; 147 of the 147 references it cites were found in a registry or an index.

Design of advanced porous graphene materials: from graphene nanomesh to 3D architectures

Jiang, Lili, Fan, Zhuangjun·2014·Nanoscale

Abstract

In order to make full utilization of the high intrinsic surface area of graphene, recently, porous graphene materials including graphene nanomesh, crumpled graphene and graphene foam, have attracted tremendous attention and research interest, owing to their exceptional porous structure (high surface area, and high pore volume) in combination with the inherent properties of graphene, such as high electronic conductivity, good thermal stability, and excellent mechanical strength. Interestingly, porous graphene materials and their derivatives have been explored in a wide range of applications in the fields of electronic and photonic devices, energy storage, gas separation/storage, oil absorption and sensors. This article reviews recent progress in the synthesis, characterization, properties, and applications of porous graphene materials. We aim to highlight the importance of designing different porous structures of graphene to meet future challenges, and the trend on future design of porous graphene materials is analyzed.

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Metadata

Authors
Jiang, L., & Fan, Z.
Venue
Nanoscale
Published
2014
Volume
6
Issue
4
Pages
1922-1945
ISSN
  • 2040-3364 (ISSN-L)
  • 2040-3372
OpenAlex
W2031311944
Cited by
686
References
147
FWCI
32.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Design of advanced porous graphene materials: from graphene nanomesh to 3D architectures. https://app.cochat.ai/papers/10.1039/c3nr04555b
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Jiang, L., & Fan, Z. (2014). Design of advanced porous graphene materials: from graphene nanomesh to 3D architectures. Nanoscale. https://doi.org/10.1039/c3nr04555b

Data sources

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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.