Evidence map›Paper›PMID 32823482›Full record

ArticlePolymers2020

Near-Linear Responsive and Wide-Range Pressure and Stretch Sensor Based on Hierarchical Graphene-Based Structures via Solvent-Free Preparation.

Jian Wang, Ryuki Suzuki, Kentaro Ogata, Takuto Nakamura, Aixue Dong, Wei Weng

Abstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

6 authors.

Jian WangCenter for Material Design Science, School of Integrated Design Engineering, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan.
Ryuki SuzukiCenter for Material Design Science, School of Integrated Design Engineering, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan.ORCID 0000-0002-8432-1121
Kentaro OgataCenter for Material Design Science, School of Integrated Design Engineering, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan.
Takuto NakamuraCenter for Material Design Science, School of Integrated Design Engineering, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan.
Aixue DongCollege of Textile and Garment, Shaoxing University, Shaoxing 312000, Zhejiang, China.ORCID 0000-0002-5510-3475
Wei WengCenter for Material Design Science, School of Integrated Design Engineering, Keio University, 3-14-1 Hiyoshi, Yokohama 223-8522, Japan.ORCID 0000-0002-9618-3010

Funding

KLL Ph.D. Program Research Grant 000144
6 · The paper itself

Abstract

Flexible and wearable electronics have huge potential applications in human motion detection, human-computer interaction, and context identification, which have promoted the rapid development of flexible sensors. So far the sensor manufacturing techniques are complex and require a large number of organic solvents, which are harmful not only to human health but also to the environment. Here, we propose a facile solvent-free preparation toward a flexible pressure and stretch sensor based on a hierarchical layer of graphene nanoplates. The resulting sensor exhibits many merits, including near-linear response, low strain detection limits to 0.1%, large strain gauge factor up to 36.2, and excellent cyclic stability withstanding more than 1000 cycles. Besides, the sensor has an extraordinary pressure range as large as 700 kPa. Compared to most of the reported graphene-based sensors, this work uses a completely environmental-friendly method that does not contain any organic solvents. Moreover, the sensor can practically realize the delicate detection of human body activity, speech recognition, and handwriting recognition, demonstrating a huge potential for wearable sensors.

Indexed as

human motion detectionpressure sensorsolvent-freestretch sensorwearable devices

Identifiers

PMID32823482
PMCPMC7465154

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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.