Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 358

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

Nitrogen‐Doped Carbon Networks for High Energy Density Supercapacitors Derived from Polyaniline Coated Bacterial Cellulose

Long, Conglai, Qi, Dongping, Wei, Tong, Yan, Jun, Jiang, Lili, Fan, Zhuangjun·2014·Advanced Functional Materials

Abstract

Bacterial cellulose (BC) is used as both template and precursor for the synthesis of nitrogen‐doped carbon networks through the carbonization of polyaniline (PANI) coated BC. The as‐obtained carbon networks can act not only as support for obtaining high capacitance electrode materials such as activated carbon (AC) and carbon/MnO 2 hybrid material, but also as conductive networks to integrate active electrode materials. As a result, the as‐assembled AC//carbon‐MnO 2 asymmetric supercapacitor exhibits a considerably high energy density of 63 Wh kg−1 in 1.0 m Na 2 SO 4 aqueous solution, higher than most reported AC//MnO 2 asymmetric supercapacitors. More importantly, this asymmetric supercapacitor also exhibits an excellent cycling performance with 92% specific capacitance retention after 5000 cycles. Those results offer a low‐cost, eco‐friendly design of electrode materials for high‐performance supercapacitors.

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.201304269

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

Show all 1 references

Metadata

Authors
Long, C., Qi, D., Wei, T., Yan, J., Jiang, L., & Fan, Z.
Venue
Advanced Functional Materials
Publisher
Wiley
Published
2014-03-18
Volume
24
Issue
25
Pages
3953-3961
ISSN
  • 1616-301X (ISSN-L)
  • 1616-3028
OpenAlex
W2007894999
Cited by
358
References
1
FWCI
16.61
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: Nitrogen‐Doped Carbon Networks for High Energy Density Supercapacitors Derived from Polyaniline Coated Bacterial Cellulose. https://app.cochat.ai/papers/10.1002/adfm.201304269
The paper
Long, C., Qi, D., Wei, T., Yan, J., Jiang, L., & Fan, Z. (2014). Nitrogen‐Doped Carbon Networks for High Energy Density Supercapacitors Derived from Polyaniline Coated Bacterial Cellulose. Advanced Functional Materials. https://doi.org/10.1002/adfm.201304269

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.