Evidence map›Paper›PMID 41302767›Full record

ArticleMicromachines2025

Robotic Drop-Coating Graphite-Copper PDMS Soft Pressure Sensor with Fabric-Integrated Electrodes for Wearable Devices.

Zeping Yu, Yunhao Zhang, Lingpu Ge, Daisuke Miyata, Zhongnan Pu, Chenghong Lu, Lei Jing

Abstract read
In one paragraph

Article in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Zeping YuGraduate School of Computer Science and Engineering, University of Aizu, Aizuwakamatsu 965-8580, Japan.ORCID 0000-0001-9963-1969
Yunhao ZhangGraduate School of Computer Science and Engineering, University of Aizu, Aizuwakamatsu 965-8580, Japan.ORCID 0009-0009-2285-0739
Lingpu GeFaculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan.ORCID 0000-0001-8105-1587
Daisuke MiyataDepartment of Computer Science and Engineering, University of Aizu, Aizuwakamatsu 965-8580, Japan.ORCID 0009-0004-6318-2996
Zhongnan PuGraduate School of Computer Science and Engineering, University of Aizu, Aizuwakamatsu 965-8580, Japan.ORCID 0009-0006-0910-9776
Chenghong LuGraduate School of Computer Science and Engineering, University of Aizu, Aizuwakamatsu 965-8580, Japan.ORCID 0000-0001-8365-8198
Lei JingDepartment of Computer Science and Engineering, University of Aizu, Aizuwakamatsu 965-8580, Japan.ORCID 0000-0002-1181-2536

Funding

JKA and its promotion funds from KEIRIN RACE. 2025New Energy and Industrial Technology Development Organization 21502121-0Toyota Motor Corporation (Japan) 2025
6 · The paper itself

Abstract

Flexible pressure sensors are essential for wearable electronics, human-machine interfaces, and soft robotics. However, conventional Polydimethylsiloxane (PDMS)-based sensors often suffer from limited conductivity, poor filler dispersion, and low structural integration with textile substrates. In this work, we present a robotic drop-coating approach for fabricating graphite-copper nanoparticle (G-CuNP)/PDMS composite pressure sensors with textile-integrated electrodes. By precisely controlling droplet deposition, a three-layer sandwiched structure was realized that ensures uniformity and scalability while avoiding the drawbacks of conventional full-line coating. The effects of filler loading and graphite nanoparticle (GNP) and copper nanoparticle (CuNP) ratios were systematically investigated, and the optimized sensor was obtained at 40 wt% total fillers with a graphite content of 55 wt%. The fabricated device exhibited high sensitivity in the low-pressure region, stable performance in the medium- and high-pressure ranges, and an exponential saturation fitting with

Indexed as

flexible pressure sensorgraphite–copper nanoparticleshuman–machine interactionPDMS compositerobotic drop-coatingtextile-integrated electrodeswearable devices

Identifiers

PMID41302767
PMCPMC12654154

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.