The DOI matches its Crossref record.
Needle-like Co3O4 Anchored on the Graphene with Enhanced Electrochemical Performance for Aqueous Supercapacitors
Abstract
We synthesized the needle-like cobalt oxide/graphene composites with different mass ratios, which are composed of cobalt oxide (Co3O4 or CoO) needle homogeneously anchored on graphene nanosheets as the template, by a facile hydrothermal method. Without the graphene as the template, the cobalt precursor tends to group into urchin-like spheres formed by many fine needles. When used as electrode materials of aqueous supercapacitor, the composites of the needle-like Co3O4/graphene (the mass ratio of graphene oxide(GO) and Co(NO3)2·6H2O is 1:5) exhibit a high specific capacitance of 157.7 F g(-1) at a current density of 0.1 A g(-1) in 2 mol L(-1) KOH aqueous solution as well as good rate capability. Meanwhile, the capacitance retention keeps about 70% of the initial value after 4000 cycles at a current density of 0.2 A g(-1). The enhancement of excellent electrochemical performances may be attributed to the synergistic effect of graphene and cobalt oxide components in the unique multiscale structure of the composites.
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.
Integrity signals
Registry
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.
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
Song, Z., Wei, Z., Wang, B., Luo, Z., Xu, S., Zhang, W., Yu, H., Li, M., Huang, Z., Zang, J., et al. (2016) · Chemistry of Materials · doi:10.1021/acs.chemmater.5b04850 · Cited by 438
Self-citation
Metadata
- Authors
- Guan, Q., Cheng, J., Wang, B., Ni, W., Gu, G., Li, X., Huang, L., Yang, G., & Nie, F.
- Venue
- ACS Applied Materials & Interfaces
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-04-21
- Volume
- 6
- Issue
- 10
- Pages
- 7626-7632
- ISSN
- 1944-8244 (ISSN-L)
- 1944-8252
- OpenAlex
- W2322970603
- Cited by
- 333
- References
- 0
- FWCI
- 16.05
- 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: Needle-like Co3O4 Anchored on the Graphene with Enhanced Electrochemical Performance for Aqueous Supercapacitors. https://app.cochat.ai/papers/10.1021/am5009369
- The paper
- Guan, Q., Cheng, J., Wang, B., Ni, W., Gu, G., Li, X., Huang, L., Yang, G., & Nie, F. (2014). Needle-like Co3O4 Anchored on the Graphene with Enhanced Electrochemical Performance for Aqueous Supercapacitors. ACS Applied Materials & Interfaces. https://doi.org/10.1021/am5009369
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.