Evidence map›Paper›PMID 32751479›Full record

ArticleSensors (Basel, Switzerland)2020

Encapsulation of Electrically Conductive Apparel Fabrics: Effects on Performance.

Sophie Wilson, Raechel Laing, Eng Wui Tan, Cheryl Wilson

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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.

Sophie WilsonMaterials Science and Technology, University of Otago, Dunedin 9016, New Zealand.ORCID 0000-0001-5906-5237
Raechel LaingMaterials Science and Technology, University of Otago, Dunedin 9016, New Zealand.ORCID 0000-0003-0607-0037
Eng Wui TanDepartment of Chemistry, University of Otago, Dunedin 9016, New Zealand.ORCID 0000-0002-7342-5494
Cheryl WilsonMaterials Science and Technology, University of Otago, Dunedin 9016, New Zealand.ORCID 0000-0003-2607-9936

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electrically conductive fabrics are achieved by functionalizing with treatments such as graphene; however, these change conventional fabric properties and the treatments are typically not durable. Encapsulation may provide a solution for this, and the present work aims to address these challenges. Next-to-skin wool and cotton knit fabrics functionalized using graphene ink were encapsulated with three poly(dimethylsiloxane)-based products. Properties known to be critical in a next-to-skin application were investigated (fabric structure, moisture transfer, electrical conductivity, exposure to transient ambient conditions, wash, abrasion, and storage). Wool and cotton fabrics performed similarly. Electrical conductivity was conferred with the graphene treatment but decreased with encapsulation. Wetting and high humidity/low temperature resulted in an increase in electrical conductivity, while decreases in electrical conductivity were evident with wash, abrasion, and storage. Each encapsulant mitigated effects of exposures but these effects differed slightly. Moisture transfer changed with graphene and encapsulants. As key performance properties of the wool and cotton fabrics following treatment with graphene and an encapsulant differed from their initial state, use as a patch integrated as part of an upper body apparel item would be acceptable.

Indexed as

Electric ConductivityGraphiteTextilesCotton FiberHumidityTemperatureWool FiberGraphitecottonelectrical conductivityencapsulationgraphemeknit fabricwearable technologywool

Identifiers

PMID32751479
PMCPMC7436089

What OpenQuestion holds

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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.