Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 242

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Network cracks-based wearable strain sensors for subtle and large strain detection of human motions

Open access
Wang, Shuai, Xiao, Peng, Liang, Yun, Zhang, Jiawei, Huang, Youju, Wu, Si, Kuo, Shiao-Wei, Chen, Tao·2018·Journal of Materials Chemistry C

Abstract

Macroscopic multilayer free-standing CNTs films/PDMS composite with cracks in the network structure displays ability for the full-range detection of human motions.

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 · 10.1039/c8tc00433a

Cites

5 of 5 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 5 references

Cited by

See all 242

Metadata

Authors
Wang, S., Xiao, P., Liang, Y., Zhang, J., Huang, Y., Wu, S., Kuo, S.-W., & Chen, T.
Venue
Journal of Materials Chemistry C
Published
2018
Volume
6
Issue
19
Pages
5140-5147
ISSN
  • 2050-7526 (ISSN-L)
  • 2050-7534
OpenAlex
W2795796969
Cited by
242
References
5
FWCI
9.34
Type
journal article
Language
en
Open access
hybrid

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: Network cracks-based wearable strain sensors for subtle and large strain detection of human motions. https://app.cochat.ai/papers/10.1039/c8tc00433a
The paper
Wang, S., Xiao, P., Liang, Y., Zhang, J., Huang, Y., Wu, S., Kuo, S.-W., & Chen, T. (2018). Network cracks-based wearable strain sensors for subtle and large strain detection of human motions. Journal of Materials Chemistry C. https://doi.org/10.1039/c8tc00433a

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.