Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 3,058

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Triboelectric Nanogenerators as New Energy Technology for Self-Powered Systems and as Active Mechanical and Chemical Sensors

Wang, Zhong Lin·2013·ACS Nano

Abstract

Triboelectrification is an effect that is known to each and every one probably since ancient Greek time, but it is usually taken as a negative effect and is avoided in many technologies. We have recently invented a triboelectric nanogenerator (TENG) that is used to convert mechanical energy into electricity by a conjunction of triboelectrification and electrostatic induction. As for this power generation unit, in the inner circuit, a potential is created by the triboelectric effect due to the charge transfer between two thin organic/inorganic films that exhibit opposite tribo-polarity; in the outer circuit, electrons are driven to flow between two electrodes attached on the back sides of the films in order to balance the potential. Since the most useful materials for TENG are organic, it is also named organic nanogenerator, which is the first using organic materials for harvesting mechanical energy. In this paper, we review the fundamentals of the TENG in the three basic operation modes: vertical contact-separation mode, in-plane sliding mode, and single-electrode mode. Ever since the first report of the TENG in January 2012, the output power density of TENG has been improved 5 orders of magnitude within 12 months. The area power density reaches 313 W/m(2), volume density reaches 490 kW/m(3), and a conversion efficiency of ∼60% has been demonstrated. The TENG can be applied to harvest all kinds of mechanical energy that is available but wasted in our daily life, such as human motion, walking, vibration, mechanical triggering, rotating tire, wind, flowing water, and more. Alternatively, TENG can also be used as a self-powered sensor for actively detecting the static and dynamic processes arising from mechanical agitation using the voltage and current output signals of the TENG, respectively, with potential applications for touch pad and smart skin technologies. To enhance the performance of the TENG, besides the vast choices of materials in the triboelectric series, from polymer to metal and to fabric, the morphologies of their surfaces can be modified by physical techniques with the creation of pyramid-, square-, or hemisphere-based micro- or nanopatterns, which are effective for enhancing the contact area and possibly the triboelectrification. The surfaces of the materials can be functionalized chemically using various molecules, nanotubes, nanowires, or nanoparticles, in order to enhance the triboelectric effect. The contact materials can be composites, such as embedding nanoparticles in a polymer matrix, which may change not only the surface electrification but also the permittivity of the materials so that they can be effective for electrostatic induction. Therefore, there are numerous ways to enhance the performance of the TENG from the materials point of view. This gives an excellent opportunity for chemists and materials scientists to do extensive study both in the basic science and in practical applications. We anticipate that a better enhancement of the output power density will be achieved in the next few years. The TENG is possible not only for self-powered portable electronics but also as a new energy technology with potential to contribute to the world energy in the near future.

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/nn404614z

Cites

3 of 3 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 3 references

Cited by

See all 3,058

Metadata

Authors
Wang, Z. L.
Venue
ACS Nano
Published
2013-10-03
Volume
7
Issue
11
Pages
9533-9557
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
OpenAlex
W2034834428
Cited by
3,058
References
3
FWCI
58.81
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: Triboelectric Nanogenerators as New Energy Technology for Self-Powered Systems and as Active Mechanical and Chemical Sensors. https://app.cochat.ai/papers/10.1021/nn404614z
The paper
Wang, Z. L. (2013). Triboelectric Nanogenerators as New Energy Technology for Self-Powered Systems and as Active Mechanical and Chemical Sensors. ACS Nano. https://doi.org/10.1021/nn404614z

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.