Evidence map›Paper›PMID 40428705›Full record

ArticleMicromachines2025

MXene-Based High-Performance Soft Pressure Sensor Using Gel-Deep Eutectic Solvent Composite.

Riku Sasaki, Kaiin Tou, Shoma Kamanoi, Junya Yoshida, Yoshihito Takabe, Yasuyuki Miura, Eri Kamiya, Ayana Hirayama, Tomohito Sekine

Abstract read
PubMed Full text at PMC Publisher
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

9 authors.

Riku SasakiGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.
Kaiin TouGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.
Shoma KamanoiGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.
Junya YoshidaGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.
Yoshihito TakabeGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.
Yasuyuki MiuraGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.
Eri KamiyaGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.
Ayana HirayamaGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.
Tomohito SekineGraduate School of Organic Materials Science, Yamagata University, 4-3-16, Jonan, Yonezawa 992-8510, Yamagata, Japan.

Funding

KAKENHI 23K13805
6 · The paper itself

Abstract

MXene, a layered nanocarbon material, exhibits excellent conductivity and solubility. Its high sensitivity also makes it useful for soft pressure sensors. However, the compatibility between sensitivity and fast responses in resistance-change sensors remains a major issue. This study developed an MXene-based high-performance soft pressure sensor using a gel-deep eutectic solvent composite. The composite conductive material exhibited excellent solubility and printability in soft device fabrication. The aim of this work was to produce a high-quality soft pressure sensor that exhibited quick responses over a wide sensitivity range for detecting applied pressure. The sensors achieved high performance in terms of a high-speed response (40 ms) and good sensitivity (-0.0109 kPa

Indexed as

composite materialdeep eutectic solventMXenepressure sensorwearable electronics

Identifiers

PMID40428705
PMCPMC12114184

What OpenQuestion holds

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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.