Evidence map›Paper›PMID 36546945›Full record

ArticleBiomimetics (Basel, Switzerland)2022

Magnetically Tunable Adhesion of Magnetoactive Elastomers' Surface Covered with Two-Level Newt-Inspired Microstructures.

Shiwei Chen, Ziyuan Qian, Xiaojiao Fu, Xuan Wu

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Shiwei ChenDepartment of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing 400030, China.
Ziyuan QianDepartment of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing 400030, China.
Xiaojiao FuDepartment of Civil Engineering and Architecture, Chongqing University of Science and Technology, Chongqing 400030, China.
Xuan WuInstitute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China.

Funding

National Natural Science Foundation of China NO.51605467 and NO.U22B2040Natural Science Foundation of Chongqing No.cstc2019jcyj-msxmX0298
6 · The paper itself

Abstract

As one of the new intelligent materials, controllable bionic adhesive materials have great application prospects in many fields, such as wearable electronic devices, wall climbing robot systems, and biomedical engineering. Inspired by the microstructure of the newt pad's surface, this paper reports a bionic adhesive surface material with controllable adhesion on dry, wet acrylic, and iron sheet surfaces. The material is prepared by mixing the PDMS matrix with micron carbonyl iron powders (CIPs) and then pouring the mixture into a female mold prepared by Photo-curing 3D Printing for curing. As the mold interior is designed with a two-level microstructure array, the material's surface not only coated a regular hexagonal column array with a side length of 250 μm and a height of 100 μm but also covered seven dome structures with a diameter of 70 μm on each column. In what follows, the adhesion force of the proposed materials contacted three different surfaces are tested with/without magnetic fields. The experimental results show that the MAEs covered with two-level bionic structures(2L-MAE) reported in this paper exhibit a stronger initial adhesion in the three types of surfaces compared to the normal one. Besides, we also found that the magnetic field will noticeably affect their adhesion performance. Generally, the 2L-MAE's adhesion will increase with the external magnetic field. When the contact surface is an iron sheet, the material adhesion will be reduced by the magnetic field.

Indexed as

bionic-inspired adhesionmagnetoactive elastomertunable adhesiontwo-level microstructure

Identifiers

PMID36546945
PMCPMC9775175

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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.