Evidence map›Paper›PMID 32738609›Full record

ReviewiScience2020

Towards Truly Wearable Systems: Optimizing and Scaling Up Wearable Triboelectric Nanogenerators.

K R Sanjaya D Gunawardhana, Nandula D Wanasekara, R D Ishara G Dharmasena

Abstract readReview
In one paragraph

Review in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

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  12. Masks for COVID-19.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

K R Sanjaya D GunawardhanaDepartment of Textile and Clothing Technology, Faculty of Engineering, University of Moratuwa, Bandaranayake Mawatha, Moratuwa 10400, Sri Lanka.
Nandula D WanasekaraDepartment of Textile and Clothing Technology, Faculty of Engineering, University of Moratuwa, Bandaranayake Mawatha, Moratuwa 10400, Sri Lanka.
R D Ishara G DharmasenaDepartment of Textile and Clothing Technology, Faculty of Engineering, University of Moratuwa, Bandaranayake Mawatha, Moratuwa 10400, Sri Lanka; Wolfson School of Mechanical Electrical and Manufacturing Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK. Electronic address: r.i.dharmasena@lboro.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Triboelectric nanogenerator (TENG) is an upcoming technology to harvest energy from ambient movements. A major focus herein is harvesting energy from human movements through wearable TENGs, which are constructed by integrating nanogenerators into clothing or accessories. Textile-based TENGs, which include fiber, yarn, and fabric-based TENG structures, account for the majority of wearable TENGs, with many designs and applications demonstrated recently. This calls for a comprehensive analysis of textile-based TENG technology, and how the state-of-the-art device optimization concepts can be deployed to construct them efficiently. Concurrently, how advanced engineering concepts and industrial manufacturing techniques, which are bound with fiber, yarn, and fabric-related developments, can be applied into the TENG context for their output enhancement is still under investigation. Herein, we fill this vital gap by analyzing the state-of-the-art developments, upcoming trends, output optimization strategies, scalability, and prospects of the textile-based TENG technology, presenting a textile engineering perspective.

Indexed as

Energy ResourcesMaterials DesignNanostructureNanotechnologySmart Textiles

Identifiers

PMID32738609
PMCPMC7394760

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.