Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 403

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

In Situ Fabrication of Porous Graphene Electrodes for High-Performance Energy Storage

Wang, Zhong-Li, Xu, Dan, Wang, Heng-Guo, Wu, Zhong, Zhang, Xin-Bo·2013·ACS Nano

Abstract

In the development of energy-storage devices, simultaneously achieving high power and large energy capacity at fast rate is still a great challenge. In this paper, the synergistic effect of structure and doping in the graphene is demonstrated for high-performance lithium storage with ulftrafast and long-cycling capabilities. By an in situ constructing strategy, hierarchically porous structure, highly conductive network, and heteroatom doping are ideally combined in one graphene electrode. Compared to pristine graphene, it is found that the degree of improvement with both structure and doping effects is much larger than the sum of that with only structure effect or doping effect. Benefitting from the synergistic effect of structure and doping, the novel electrodes can deliver a high-power density of 116 kW kg(-1) while the energy density remains as high as 322 Wh kg(-1) at 80 A g(-1) (only 10 s to full charge), which provides an electrochemical storage level with the power density of a supercapacitor and the energy density of a battery, bridging the gap between them. Furthermore, the optimized electrodes exhibit long-cycling capability with nearly no capacity loss for 3000 cycles and wide temperature features with high capacities ranging from -20 to 55 °C.

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/nn3057388

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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

Cites

Cited by

See all 403

Metadata

Authors
Wang, Z.-L., Xu, D., Wang, H.-G., Wu, Z., & Zhang, X.-B.
Venue
ACS Nano
Published
2013-02-18
Volume
7
Issue
3
Pages
2422-2430
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2320478799
Cited by
403
References
1
FWCI
41.14
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

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.