Evidence map›Paper›PMID 38068026›Full record

ArticleMaterials (Basel, Switzerland)2023

The Magneto-Mechanical Hyperelastic Property of Isotropic Magnetorheological Elastomers with Hybrid-Size Magnetic Particles.

Leizhi Wang, Ke Zhang, Zhaobo Chen

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 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

3 authors.

Leizhi WangSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China.
Ke ZhangSchool of Chemical Engineering and Technology, Harbin Institute of Technology, Harbin 150001, China.
Zhaobo ChenSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China.

Funding

National Natural Science Foundation of China 11772103
6 · The paper itself

Abstract

Isotropic magnetorheological elastomers (MREs) with hybrid-size particles are proposed to tailor the zero-field elastic modulus and the relative magnetorheological rate. The hyperelastic magneto-mechanical property of MREs with hybrid-size CIPs (carbonyl iron particles) was experimentally investigated under large strain, which showed differential hyperelastic mechanical behavior with different hybrid-size ratios. Quasi-static magneto-mechanical compression tests corresponding to MREs with different hybrid size ratios and mass fractions were performed to analyze the effects of hybrid size ratio, magnetic flux density, and CIP mass fraction on the magneto-mechanical properties. An extended Knowles magneto-mechanical hyperelastic model based on magnetic energy, coupling the magnetic interaction, is proposed to predict the influence of mass fraction, hybrid size ratio, and magnetic flux density on the magneto-mechanical properties of isotropic MRE. Comparing the experimental and predicted results, the proposed model can accurately evaluate the quasi-static compressive magneto-mechanical properties, which show that the predicted mean square deviations of the magneto-mechanical constitutive curves for different mass fractions are all in the range of 0.9-1. The results demonstrate that the proposed hyperelastic magneto-mechanical model, evaluating the magneto-mechanical properties of isotropic MREs with hybrid-size CIPs, has a significant stress-strain relationship. The proposed model is important for the characterization of magneto-mechanical properties of MRE-based smart devices.

Indexed as

extended Knowles modelhybrid sizehyperelastic propertyisotropic MREmagneto–mechanical compression

Identifiers

PMID38068026
PMCPMC10707293

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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.