Evidence map›Paper›PMID 39597156›Full record

ArticleMicromachines2024

3D-Printed Multi-Axis Alignment Airgap Dielectric Layer for Flexible Capacitive Pressure Sensor.

Jeong-Beom Ko, Soo-Wan Kim, Hyeon-Beom Kim, Hyeon-Yun Jeong, Su-Yeong Moon, Young-Jin Yang

Abstract read
In one paragraph

Article in Micromachines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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.

Jeong-Beom KoClean Energy Transition Group, Korea Institute of Industrial Technology (KITECH), Jeju 63243, Republic of Korea.
Soo-Wan KimClean Energy Transition Group, Korea Institute of Industrial Technology (KITECH), Jeju 63243, Republic of Korea.
Hyeon-Beom KimClean Energy Transition Group, Korea Institute of Industrial Technology (KITECH), Jeju 63243, Republic of Korea.
Hyeon-Yun JeongClean Energy Transition Group, Korea Institute of Industrial Technology (KITECH), Jeju 63243, Republic of Korea.
Su-Yeong MoonClean Energy Transition Group, Korea Institute of Industrial Technology (KITECH), Jeju 63243, Republic of Korea.
Young-Jin YangClean Energy Transition Group, Korea Institute of Industrial Technology (KITECH), Jeju 63243, Republic of Korea.

Funding

Korea Institute of Industrial Technology Kitech UR-24-0027
6 · The paper itself

Abstract

Flexible pressure sensors are increasingly recognized for their potential use in wearable electronic devices, attributed to their sensitivity and broad pressure response range. Introducing surface microstructures can notably enhance sensitivity; however, the pressure response range remains constrained by the limited volume of the compressible structure. To overcome this limitation, this study implements an aligned airgap structure fabricated using 3D printing technology. This structure, designed with a precisely aligned triaxial airgap configuration, offers high deformability under pressure, substantially broadening the pressure response range and improving sensitivity. This study analyzes the key structural parameters-the number of axes and pore size-that influence the compressibility and stability of the dielectric material. The results indicate that the capacitive pressure sensor with an aligned airgap structure, manufactured via 3D printing, exhibits a wide operating pressure range (50 Pa to 500 kPa), rapid response time (100 ms), wide limit of detection (50 Pa), and approximately 21 times enhancement in sensitivity (~0.019 kPa

Indexed as

3D printingalignment airgap dielectriccapacitive pressure sensorflexible sensor

Identifiers

PMID39597156
PMCPMC11596244

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.