Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 314

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

Waterproof Fabric‐Based Multifunctional Triboelectric Nanogenerator for Universally Harvesting Energy from Raindrops, Wind, and Human Motions and as Self‐Powered Sensors

Open access
Lai, Ying‐Chih, Hsiao, Yung‐Chi, Wu, Hsing‐Mei, Wang, Zhong Lin·2019·Advanced Science

Abstract

Developing nimble, shape‐adaptable, conformable, and widely implementable energy harvesters with the capability to scavenge multiple renewable and ambient energy sources is highly demanded for distributed, remote, and wearable energy uses to meet the needs of internet of things. Here, the first single waterproof and fabric‐based multifunctional triboelectric nanogenerator (WPF‐MTENG) is presented, which can produce electricity from both natural tiny impacts (rain and wind) and body movements, and can not only serve as a flexible, adaptive, wearable, and universal energy collector but also act as a self‐powered, active, fabric‐based sensor. The working principle comes from a conjunction of contact triboelectrification and electrostatic induction during contact/separation of internal soft fabrics. The structural/material designs of the WPF‐MTENG are systematically studied to optimize its performance, and its outputs under different conditions of rain, wind, and various body movements are comprehensively investigated. Its applicability is practically demonstrated in various objects and working situations to gather ambient energy. Lastly, a WPF‐MTENG‐based keypad as self‐powered human–system interfaces is demonstrated on a garment for remotely controlling a music‐player system. This multifunctional WPF‐MTENG, which is as flexible as clothes, not only presents a promising step toward democratic collections of alternative energy but also provides a new vision for wearable technologies.

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/advs.201801883

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

Cited by

See all 314

Metadata

Authors
Lai, Y., Hsiao, Y., Wu, H., & Wang, Z. L.
Venue
Advanced Science
Publisher
Wiley
Published
2019-01-04
Volume
6
Issue
5
Pages
1801883-1801883
ISSN
2198-3844 (ISSN-L)
OpenAlex
W2907826179
Cited by
314
References
3
FWCI
15.42
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

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.