Evidence map›Paper›PMID 36295785›Full record

ArticleMembranes2022

Study on the Actuation Properties of Polyurethane Fiber Membranes Filled with PEG-SWNTs Dielectric Microcapsules.

Gang Lu, Changgeng Shuai, Yinsong Liu, Xue Yang

Open access · goldAbstract read
In one paragraph

Article in Membranes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 57% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Review
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

4 authors at 1 institution in 1 country.

Gang LuInstitute of Noise and Vibration, Naval University of Engineering, Wuhan 430033, China.ORCID 0000-0002-8542-6590
Changgeng ShuaiInstitute of Noise and Vibration, Naval University of Engineering, Wuhan 430033, China.
Yinsong LiuInstitute of Noise and Vibration, Naval University of Engineering, Wuhan 430033, China.
Xue YangInstitute of Noise and Vibration, Naval University of Engineering, Wuhan 430033, China.
Naval University of Engineering · CN

Funding

National Natural Science Foundation of China 52171328
6 · The paper itself

Abstract

Polyurethane dielectric elastomer (PUDE), a typical representative of emerging intelligent materials, has advantages, such as good elasticity and flexibility, fast response speed, high electromechanical conversion efficiency, and strong environmental tolerance. It has promising applications in underwater bionic actuators, but its electromechanical properties should be improved further. In this context, the design of polyethylene glycol (PEG) single-walled carbon nanotube (SWNTs) dielectric microcapsules was adopted to balance the problem of contradictions, which conventional dielectric modification methods face between comprehensive properties (e.g., dielectric properties and modulus). Moreover, the dielectric microcapsule was evenly filled into the polyurethane fiber by coaxial spinning technology to enhance the actuation performance and instability of the electrical breakdown threshold of conventional polyurethane dielectric modification. It was revealed that the dielectric microcapsules were oriented in the polyurethane fiber, and the actuation performance of the composite fiber membrane was significantly better than that of the polyurethane fiber membrane filled with SWNTs, thus confirming that the filling design of the dielectric microcapsules in polyurethane fiber could have certain technical advantages. On that basis, this study provides a novel idea for the dielectric modification of polyurethane.

Indexed as

actuation propertiescoaxial spinningdielectric microcapsulefiber membranepolyurethane dielectric elastomer

Identifiers

PMID36295785
PMCPMC9606993
OpenAlexW4307161881

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.