Evidence map›Paper›PMID 35161157›Full record

ArticleMaterials (Basel, Switzerland)2022

Comparison of Pressure Sensing Properties of Carbon Nanotubes and Carbon Black Polymer Composites.

Jongchan Yoo, Dong-Young Kim, Hyunwoo Kim, Oh-Nyoung Hur, Sung-Hoon Park

Open access · goldAbstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.0field-weighted citation impact, top 14% of its field
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

6 citing papers in PubMed, 25 citations in OpenAlex.

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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

5 authors at 1 institution in 1 country.

Jongchan YooDepartment of Mechanical Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Korea.
Dong-Young KimDepartment of Mechanical Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Korea.
Hyunwoo KimDepartment of Mechanical Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Korea.
Oh-Nyoung HurDepartment of Mechanical Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Korea.
Sung-Hoon ParkDepartment of Mechanical Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Korea.ORCID 0000-0001-5683-9882
Soongsil University · KR

Funding

National Research Foundation of Korea Grant 2020R1A2C1013489
6 · The paper itself

Abstract

Polymer composites containing conductive fillers that utilize the piezoresistive effect can be employed in flexible pressure sensors. Depending on the filler used, different characteristics of a pressure sensor such as repeatability, sensitivity, and hysteresis can be determined. To confirm the variation of the pressure sensing tendency in accordance with the dimensions of the filler, carbon black (CB) and carbon nanotubes (CNTs) were used as representative 0-dimension and 1-dimension conductive fillers, respectively. The piezoresistive effect was exploited to analyze the process of resistance change according to pressure using CB/PDMS (polydimethylsiloxane) and CNT/PDMS composites. The electrical characteristics observed for each filler were confirmed to be in accordance with its content. The pressure sensitivity of each composite was optimized, and the pressure-sensing mechanism that explains the difference in sensitivity is presented. Through repeated compression experiments, the hysteresis and repeatability of the pressure-sensing properties were examined.

Indexed as

carbon blackcarbon nanotubepiezoresistive effectpolymer compositepressure sensor

Identifiers

PMID35161157
PMCPMC8838471
OpenAlexW4210731463

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.