Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 648

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

Triboelectric Nanogenerator for Harvesting Wind Energy and as Self-Powered Wind Vector Sensor System

Yang, Ya, Zhu, Guang, Zhang, Hulin, Chen, Jun, Zhong, Xiandai, Lin, Zong-Hong, Su, Yuanjie, Bai, Peng, Wen, Xiaonan, Wang, Zhong Lin·2013·ACS Nano

Abstract

We report a triboelectric nanogenerator (TENG) that plays dual roles as a sustainable power source by harvesting wind energy and as a self-powered wind vector sensor system for wind speed and direction detection. By utilizing the wind-induced resonance vibration of a fluorinated ethylene-propylene film between two aluminum foils, the integrated TENGs with dimensions of 2.5 cm × 2.5 cm × 22 cm deliver an output voltage up to 100 V, an output current of 1.6 μA, and a corresponding output power of 0.16 mW under an external load of 100 MΩ, which can be used to directly light up tens of commercial light-emitting diodes. Furthermore, a self-powered wind vector sensor system has been developed based on the rationally designed TENGs, which is capable of detecting the wind direction and speed with a sensitivity of 0.09 μA/(m/s). This work greatly expands the applicability of TENGs as power sources for self-sustained electronics and also self-powered sensor systems for ambient wind detection.

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 · 10.1021/nn4043157

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

Cited by

See all 648

Metadata

Authors
Yang, Y., Zhu, G., Zhang, H., Chen, J., Zhong, X., Lin, Z.-H., Su, Y., Bai, P., Wen, X., & Wang, Z. L.
Venue
ACS Nano
Published
2013-09-17
Volume
7
Issue
10
Pages
9461-9468
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2063013044
Cited by
648
References
1
FWCI
18.07
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

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.