Evidence map›Paper›PMID 37985370›Full record

ArticleACS applied materials & interfaces2023

Wear-Resistant Smart Textiles Using Nylon-11 Triboelectric Yarns.

Piotr K Szewczyk, Tommaso Busolo, Sohini Kar-Narayan, Urszula Stachewicz

Abstract read
In one paragraph

Article in ACS applied materials & interfaces, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Piotr K SzewczykFaculty of Metals Engineering and Industrial Computer Science, AGH University of Krakow, Krakow 30-059, Poland.ORCID 0000-0003-1441-7387
Tommaso BusoloDepartment of Materials Science & Metallurgy, University of Cambridge, Cambridge CB3 0FS, United Kingdom.ORCID 0000-0003-1815-9557
Sohini Kar-NarayanDepartment of Materials Science & Metallurgy, University of Cambridge, Cambridge CB3 0FS, United Kingdom.ORCID 0000-0002-8151-1616
Urszula StachewiczFaculty of Metals Engineering and Industrial Computer Science, AGH University of Krakow, Krakow 30-059, Poland.ORCID 0000-0001-5102-8685

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ever-increasing demand for self-powered systems such as glucose biosensors and mixed reality devices has sparked significant interest in triboelectric generators, which hold large potential as renewable energy solutions. Our study explores new methods for integrating energy-harvesting capabilities into smart textiles by developing strong and efficient yarns that can convert mechanical energy into electrical energy through a triboelectric effect. Specifically, we focused on Nylon-11 (PA11), a material known for its crystalline structure well-suited for generating a powerful triboelectric response. To achieve this, we created triboelectric yarns by electrospinning PA11 fibers onto conductive carbon yarns, enabling energy-harvesting applications. Extensive testing demonstrated that these yarns possess exceptional durability, surpassing real-life usage requirements while experiencing minimal degradation. Additionally, we developed a prototype haptic device by interweaving tribopositive PA11 and tribonegative poly(vinylidene fluoride) (PVDF) triboelectric yarns. Our research has successfully yielded durable and efficient yarns with strong energy-harvesting capabilities, opening up possibilities for integrating smart textiles into practical scenarios. These technologies are promising steps to achieve greener and more reliable self-powered systems.

Indexed as

electrospinningenergy harvestingPA11smart textilestriboelectric devices

Identifiers

PMID37985370
PMCPMC10711711

What OpenQuestion holds

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LicenceCC BY
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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.