Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 451

The DOI matches its Crossref record.

Template-Assisted Low Temperature Synthesis of Functionalized Graphene for Ultrahigh Volumetric Performance Supercapacitors

Yan, Jun, Wang, Qian, Wei, Tong, Jiang, Lili, Zhang, Milin, Jing, Xiaoyan, Fan, Zhuangjun·2014·ACS Nano

Abstract

We demonstrated the fabrication of functionalized graphene nanosheets via low temperature (300 °C) treatment of graphite oxide with a slow heating rate using Mg(OH)2 nanosheets as template. Because of its dented sheet with high surface area, a certain amount of oxygen-containing groups, and low pore volume, the as-obtained graphene delivers both ultrahigh specific gravimetric and volumetric capacitances of 456 F g(-1) and 470 F cm(-3), almost 3.7 times and 3.3 times higher than hydrazine reduced graphene, respectively. Especially, the obtained volumetric capacitance is the highest value so far reported for carbon materials in aqueous electrolytes. More importantly, the assembled supercapacitor exhibits an ultrahigh volumetric energy density of 27.2 Wh L(-1), which is among the highest values for carbon materials in aqueous electrolytes, as well as excellent cycling stability with 134% of its initial capacitance after 10,000 cycles. Therefore, the present work holds a great promise for future design and large-scale production of high performance graphene electrodes for portable energy storage devices.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/nn500497k

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 451

Metadata

Authors
Yan, J., Wang, Q., Wei, T., Jiang, L., Zhang, M., Jing, X., & Fan, Z.
Venue
ACS Nano
Published
2014-04-17
Volume
8
Issue
5
Pages
4720-4729
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2330286188
Cited by
451
References
0
FWCI
19.64
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Template-Assisted Low Temperature Synthesis of Functionalized Graphene for Ultrahigh Volumetric Performance Supercapacitors. https://app.cochat.ai/papers/10.1021/nn500497k
The paper
Yan, J., Wang, Q., Wei, T., Jiang, L., Zhang, M., Jing, X., & Fan, Z. (2014). Template-Assisted Low Temperature Synthesis of Functionalized Graphene for Ultrahigh Volumetric Performance Supercapacitors. ACS Nano. https://doi.org/10.1021/nn500497k

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.