Evidence map›Paper›PMID 37765670›Full record

ArticlePolymers2023

Wearable Capacitive Tactile Sensor Based on Porous Dielectric Composite of Polyurethane and Silver Nanowire.

Gen-Wen Hsieh, Chih-Yang Chien

Abstract read
In one paragraph

Article in Polymers, 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. Review
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

2 authors.

Gen-Wen HsiehInstitute of Lighting and Energy Photonics, College of Photonics, National Yang Ming Chiao Tung University, 301, Gaofa 3rd Road, Section 2, Guiren District, Tainan 71150, Taiwan.ORCID 0000-0001-8457-0948
Chih-Yang ChienInstitute of Photonic System, College of Photonics, National Yang Ming Chiao Tung University, 301, Section 2, Gaofa 3rd Road, Guiren District, Tainan 71150, Taiwan.

Funding

National Science and Technology Council, Taiwan NSTC 110-2221-E-A49-141National Science and Technology Council, Taiwan NSTC 111-2221-E-A49-183
6 · The paper itself

Abstract

In recent years, the implementation of wearable and biocompatible tactile sensing elements with sufficient response into healthcare, medical detection, and electronic skin/amputee prosthetics has been an intriguing but challenging quest. Here, we propose a flexible all-polyurethane capacitive tactile sensor that utilizes a salt crystal-templated porous elastomeric framework filling with silver nanowire as the composite dielectric material, sandwiched by a set of polyurethane films covering silver nanowire networks as electrodes. With the aids of these cubic air pores and conducting nanowires, the fabricated capacitive tactile sensor provides pronounced enhancement of both sensor compressibility and effective relative dielectric permittivity across a broad pressure regime (from a few Pa to tens of thousands of Pa). The fabricated silver nanowire-porous polyurethane sensor presents a sensitivity improvement of up to 4-60 times as compared to a flat polyurethane device. An ultrasmall external stimulus as light as 3 mg, equivalent to an applied pressure of ∼0.3 Pa, can also be clearly recognized. Our all-polyurethane capacitive tactile sensor based on a porous dielectric framework hybrid with conducting nanowire reveals versatile potential applications in physiological activity detection, arterial pulse monitoring, and spatial pressure distribution, paving the way for wearable electronics and artificial skin.

Indexed as

capacitive tactile sensordielectric compositeporous polyurethanesilver nanowirewearable electronic

Identifiers

PMID37765670
PMCPMC10535873

What OpenQuestion holds

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LicenceCC BY
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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.