Evidence map›Paper›PMID 33916602›Full record

ArticleSensors (Basel, Switzerland)2021

Ultrasensitive Strain Sensor Based on Pre-Generated Crack Networks Using Ag Nanoparticles/Single-Walled Carbon Nanotube (SWCNT) Hybrid Fillers and a Polyester Woven Elastic Band.

Yelin Ko, Ji-Seon Kim, Chi Cuong Vu, Jooyong Kim

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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. Article
  2. Article
  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.

Yelin KoDepartment of Organic Materials and Fiber Engineering, Soongsil University, Seoul 06978, Korea.
Ji-Seon KimDepartment of Smart Wearables Engineering, Soongsil University, Seoul 06978, Korea.
Chi Cuong VuDepartment of Organic Materials and Fiber Engineering, Soongsil University, Seoul 06978, Korea.
Jooyong KimDepartment of Organic Materials and Fiber Engineering, Soongsil University, Seoul 06978, Korea.ORCID 0000-0003-1969-5730

Funding

Korea Institute for Advancement of Technology P0002397National Research Foundation of Korea NRF-2018S1A5A8027072
6 · The paper itself

Abstract

Flexible strain sensors are receiving a great deal of interest owing to their prospective applications in monitoring various human activities. Among various efforts to enhance the sensitivity of strain sensors, pre-crack generation has been well explored for elastic polymers but rarely on textile substrates. Herein, a highly sensitive textile-based strain sensor was fabricated via a dip-coat-stretch approach: a polyester woven elastic band was dipped into ink containing single-walled carbon nanotubes coated with silver paste and pre-stretched to generate prebuilt cracks on the surface. Our sensor demonstrated outstanding sensitivity (a gauge factor of up to 3550 within a strain range of 1.5-5%), high stability and durability, and low hysteresis. The high performance of this sensor is attributable to the excellent elasticity and woven structure of the fabric substrate, effectively generating and propagating the prebuilt cracks. The strain sensor integrated into firefighting gloves detected detailed finger angles and cyclic finger motions, demonstrating its capability for subtle human motion monitoring. It is also noteworthy that this novel strategy is a very quick, straightforward, and scalable method of fabricating strain sensors, which is extremely beneficial for practical applications.

Indexed as

Metal NanoparticlesNanotubes, CarbonHumansMovementPolyestersProspective StudiesSilverNanotubes, CarbonPolyestersSilverelastic bande-textilepre-crack generationsilver pastessingle-walled carbon nanotubes (SWCNTs)strain sensorwoven fabric

Identifiers

PMID33916602
PMCPMC8038452

What OpenQuestion holds

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LicenceCC BY
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.