Evidence map›Paper›PMID 31731558›Full record

ArticleMicromachines2019

Requirements for Durability Improvement of Conductive Patterns Permeated in Textiles under Cyclic Tensile Deformation.

Tomoya Koshi, Ken-Ichi Nomura, Manabu Yoshida

Abstract read
In one paragraph

Article in Micromachines, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. 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.

Tomoya KoshiSensing System Research Center (SSRC), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565, Japan.ORCID 0000-0003-3511-5740
Ken-Ichi NomuraSensing System Research Center (SSRC), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565, Japan.ORCID 0000-0001-9459-1101
Manabu YoshidaSensing System Research Center (SSRC), National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Higashi, Tsukuba, Ibaraki 305-8565, Japan.ORCID 0000-0002-9038-6722

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conductive patterns on textiles are one of the key components for electronic textiles (E-textiles). The patterns with deeper permeation of inks into the textiles show better durability against cyclic tensile deformation. However, other requirements for improving the durability and the behavior of resistance under deformation are still unclear. In this study, the resistance during cyclic tensile deformation was measured with changing conditions, and the resistance variation was analyzed while considering the stress variation. Silver inks were printed on a plain weave, and the pattern width and tensile direction against weft yarns were changed. Measurements confirmed that the resistance increased less with wider pattern widths and when the tensile direction was horizontal to the axis of the weft yarns. Through scanning electron microscopy (SEM) observation, we also confirmed that the growth rate of cracks, at the crossing point of yarns, was changed by the tensile direction. These results indicate that the durability is improved when the electricity path redundancy within the pattern is robust, and the crack growth rate at the yarn crossing points is low. The analysis also confirmed both increasing and decreasing behavior of resistance during stretching in the cyclic tensile deformation, indicating the behavior results from the stress variation of a plain weave.

Indexed as

conductive patternE-textilesflexible electronicspermeationprinting process

Identifiers

PMID31731558
PMCPMC6915606

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Registered trials

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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.