The DOI matches its Crossref record.
Shear properties of a magnetorheological elastomer
Abstract
This paper presents an experiment testing the damped free vibration of a system composed of a magnetorheological elastomer and a mass. The goal of this experiment was to obtain the dependence of the natural frequency and the damping ratio of the structure on the applied magnetic field. The shear properties, including the shear storage modulus and the damping factor, were therefore determined. The experimental results revealed that the shear storage modulus could reach a value of 60% of the zero-field modulus and was dominated by the magnetic field, but the change in the damping factor could be neglected. Furthermore, when the field was moderate and saturation did not occur, the shear storage modulus increased proportionally with the applied field. This interesting phenomenon was analysed, and it is suggested that the subquadratic field dependence, which arises from the saturation of the magnetization near the poles of closely spaced pairs of spheres, must be taken into consideration.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Giant magnetoelastic effect in soft systems for bioelectronics
Zhou, Y., Zhao, X., Xu, J., Fang, Y., Chen, G., Song, Y., Li, S., & Chen, J. (2021) · Nature Materials · doi:10.1038/s41563-021-01093-1 · Cited by 459
Magnetic field sensitive functional elastomers with tuneable elastic modulus
Varga, Z., Filipcsei, G., & Zrínyi, M. (2006) · Polymer · doi:10.1016/j.polymer.2005.10.139 · Cited by 410
A review on magneto-mechanical characterizations of magnetorheological elastomers
Bastola, A. K., & Hossain, M. (2020) · Composites Part B: Engineering · doi:10.1016/j.compositesb.2020.108348 · Cited by 357
Metadata
- Authors
- Zhou, G. Y.
- Venue
- Smart Materials and Structures
- Publisher
- IOP Publishing
- Published
- 2003-01-27
- Volume
- 12
- Issue
- 1
- Pages
- 139-146
- ISSN
- 0964-1726 (ISSN-L)
- OpenAlex
- W2058601265
- Cited by
- 252
- References
- 0
- FWCI
- 30.48
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Shear properties of a magnetorheological elastomer. https://app.cochat.ai/papers/10.1088/0964-1726/12/1/316
- The paper
- Zhou, G. Y. (2003). Shear properties of a magnetorheological elastomer. Smart Materials and Structures. https://doi.org/10.1088/0964-1726/12/1/316
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.