Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 469

The DOI matches its Crossref record.

Design and Synthesis of Hierarchical Nanowire Composites for Electrochemical Energy Storage

Chen, Zheng, Qin, Yaochun, Weng, Ding, Xiao, Qiangfeng, Peng, Yiting, Wang, Xiaolei, Li, Hexing, Wei, Fei, Lu, Yunfeng·2009·Advanced Functional Materials

Abstract

Nanocomposites of interpenetrating carbon nanotubes and vanadium pentoxide (V 2 O 5) nanowires networks are synthesized via a simple in situ hydrothermal process. These fibrous nanocomposites are hierarchically porous with high surface area and good electric conductivity, which makes them excellent material candidates for supercapacitors with high energy density and power density. Nanocomposites with a capacitance up to 440 and 200 F g−1 are achieved at current densities of 0.25 and 10 A g−1, respectively. Asymmetric devices based on these nanocomposites and aqueous electrolyte exhibit an excellent charge/discharge capability, and high energy densities of 16 W h kg−1 at a power density of 75 W kg−1 and 5.5 W h kg−1 at a high power density of 3 750 W kg−1. This performance is a significant improvement over current electrochemical capacitors and is highly competetive with Ni–MH batteries. This work provides a new platform for high‐density electrical‐energy storage for electric vehicles and other applications.

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 · 10.1002/adfm.200900971

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 469

Metadata

Authors
Chen, Z., Qin, Y., Weng, D., Xiao, Q., Peng, Y., Wang, X., Li, H., Wei, F., & Lu, Y.
Venue
Advanced Functional Materials
Publisher
Wiley
Published
2009-10-30
Volume
19
Issue
21
Pages
3420-3426
ISSN
  • 1616-301X (ISSN-L)
  • 1616-3028
OpenAlex
W2119982671
Cited by
469
References
0
FWCI
11.74
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: Design and Synthesis of Hierarchical Nanowire Composites for Electrochemical Energy Storage. https://app.cochat.ai/papers/10.1002/adfm.200900971
The paper
Chen, Z., Qin, Y., Weng, D., Xiao, Q., Peng, Y., Wang, X., Li, H., Wei, F., & Lu, Y. (2009). Design and Synthesis of Hierarchical Nanowire Composites for Electrochemical Energy Storage. Advanced Functional Materials. https://doi.org/10.1002/adfm.200900971

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.