Evidence map›Paper›PMID 37766971›Full record

ArticleiScience2023

Giant flexoelectric response of uniformly dispersed BT-PVDF composite films induced by SDS-assisted treatment.

Yujie Wei, Ying Yu, Yuxin Zuo, Zhikun Li, Zhiqing Gu, Hongli Chen, Yang Yang, Chuncheng Zuo

Abstract read
In one paragraph

Article in iScience, 2023. 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

8 authors.

Yujie WeiSchool of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310000, China.
Ying YuCollege of Information Science and Engineering, Jiaxing University, Jiaxing, Zhejiang 314000, China.
Yuxin ZuoJiaxing Nanhu University, Jiaxing 314001, China.
Zhikun LiSchool of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310000, China.
Zhiqing GuCollege of Information Science and Engineering, Jiaxing University, Jiaxing, Zhejiang 314000, China.
Hongli ChenSchool of Mechanical Engineering, Zhejiang Sci-Tech University, Hangzhou, Zhejiang 310000, China.
Yang YangSchool of Mechanical and Aerospace Engineering, Jilin University, Changchun 130000, China.
Chuncheng ZuoCollege of Information Science and Engineering, Jiaxing University, Jiaxing, Zhejiang 314000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Polymer-ceramic composites are commonly used as flexoelectric films. In existing studies, the flexoelectric effect of composites are generally improved by adjusting the material structures or adding ferroelectric materials. Further improvement of flexoelectric response has encountered a bottleneck. Considering from a new perspective, this study innovatively proposes to prepare the uniformly dispersed BT-PVDF composite films with giant flexoelectric response by surfactant SDS-assisted treatment. According to the engineering applications, tilt sensors have been fabricated with the SDS/BT-PVDF composite films. The prepared tilt sensors can accurately sense the tilt change in a small-angle range (0-10°) between the coaxial connecting parts, the response signal changes significantly (49.25-72.35 mV/°), and the response speed can reach 0.166 s. The research provides a new idea for improving the flexoelectric response and also paves a way for developing tilt sensors through a low-cost, facile, and reliable method, showing potential applications including bending sensing and structural health monitoring.

Indexed as

Applied physicsMaterials sciencePhysics

Identifiers

PMID37766971
PMCPMC10520832

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.