Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 542

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Flexible and durable wood-based triboelectric nanogenerators for self-powered sensing in athletic big data analytics

Open access
Luo, Jianjun, Wang, Ziming, Xu, Liang, Wang, Aurelia Chi, Han, Kai, Jiang, Tao, Lai, Qingsong, Bai, Yu, Tang, Wei, Fan, Feng Ru, Wang, Zhong Lin·2019·Nature Communications

Abstract

In the new era of internet of things, big data collection and analysis based on widely distributed intelligent sensing technology is particularly important. Here, we report a flexible and durable wood-based triboelectric nanogenerator for self-powered sensing in athletic big data analytics. Based on a simple and effective strategy, natural wood can be converted into a high-performance triboelectric material with excellent mechanical properties, such as 7.5-fold enhancement in strength, superior flexibility, wear resistance and processability. The electrical output performance is also enhanced by more than 70% compared with natural wood. A self-powered falling point distribution statistical system and an edge ball judgement system are further developed to provide training guidance and real-time competition assistance for both athletes and referees. This work can not only expand the application area of the self-powered system to smart sport monitoring and assisting, but also promote the development of big data analytics in intelligent sports industry.

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 · 10.1038/s41467-019-13166-6

Cites

4 of 4 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 4 references

Cited by

See all 542

Metadata

Authors
Luo, J., Wang, Z., Xu, L., Wang, A. C., Han, K., Jiang, T., Lai, Q., Bai, Y., Tang, W., Fan, F. R., & Wang, Z. L.
Venue
Nature Communications
Published
2019-11-26
Volume
10
Issue
1
Pages
5147-5147
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2991376568
Cited by
542
References
4
FWCI
19.49
Type
journal article
Language
en
Open access
gold

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: Flexible and durable wood-based triboelectric nanogenerators for self-powered sensing in athletic big data analytics. https://app.cochat.ai/papers/10.1038/s41467-019-13166-6
The paper
Luo, J., Wang, Z., Xu, L., Wang, A. C., Han, K., Jiang, T., Lai, Q., Bai, Y., Tang, W., Fan, F. R., & Wang, Z. L. (2019). Flexible and durable wood-based triboelectric nanogenerators for self-powered sensing in athletic big data analytics. Nature Communications. https://doi.org/10.1038/s41467-019-13166-6

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.