Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 170

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

Facile Synthesis of 3D Graphene Flowers for Ultrasensitive and Highly Reversible Gas Sensing

Wu, Jin, Feng, Shuanglong, Wei, Xingzhan, Shen, Jun, Lu, Wenqiang, Shi, Haofei, Tao, Kai, Lu, Shirong, Sun, Tai, Yu, Leyong, Du, Chunlei, Miao, Jianmin, Norford, Leslie K.·2016·Advanced Functional Materials

Abstract

Fabrication of nanostructured graphene (Gr) for gas sensing applications has become increasingly attractive. For the first time, 3D graphene flowers (GF) cluster patterns are grown directly on an Ni foam substrate by inexpensive homebuilt microwave plasma‐enhanced chemical vapor deposition (MPCVD) using the gas mixture H 2/C 2 H 4 O 2@Ar as a precursor. The interim morphologies of the synthesized GF are investigated and the growth mechanism of the GF film is proposed. The GF are decomposed to few‐layer Gr sheets by ultrasonication in ethanol. For the first time, MPCVD‐synthesized Gr is exploited to fabricate a gas sensor that exhibits an ultrahigh sensitivity of 133.2 ppm−1 to NO 2. Outstanding sensor responses of 1411% and 101% to 10 ppm and 200 ppb NO 2, respectively, are achieved. Furthermore, a low theoretical detection limit of 785 ppt NO 2 is achieved. An ultrafast (within 2 s) recovery is observed at room temperature, and an imbedded microheater is employed to improve the selectivity of NO 2 detection relative to humidity. This work represents a simple, clean, and efficient route to synthesize large‐area cauliflower Gr for gas detection with high performance, including ultrahigh sensitivity, good selectivity, fast recovery, and reversibility.

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.201603598

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

Cited by

See all 170

Metadata

Authors
Wu, J., Feng, S., Wei, X., Shen, J., Lu, W., Shi, H., Tao, K., Lu, S., Sun, T., Yu, L., Du, C., Miao, J., & Norford, L. K.
Venue
Advanced Functional Materials
Publisher
Wiley
Published
2016-09-14
Volume
26
Issue
41
Pages
7462-7469
ISSN
  • 1616-301X (ISSN-L)
  • 1616-3028
OpenAlex
W2520518317
Cited by
170
References
1
FWCI
9.15
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: Facile Synthesis of 3D Graphene Flowers for Ultrasensitive and Highly Reversible Gas Sensing. https://app.cochat.ai/papers/10.1002/adfm.201603598
The paper
Wu, J., Feng, S., Wei, X., Shen, J., Lu, W., Shi, H., Tao, K., Lu, S., Sun, T., Yu, L., Du, C., Miao, J., & Norford, L. K. (2016). Facile Synthesis of 3D Graphene Flowers for Ultrasensitive and Highly Reversible Gas Sensing. Advanced Functional Materials. https://doi.org/10.1002/adfm.201603598

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.