Analytical modeling of a magnetoactive elastomer unimorph

Tan Pan, Rui Leng, Oliver Uitz, Carolyn Seepersad, Zoubeida Ounaies, Mary Frecker

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Magnetoactive elastomers (MAEs) are capable of large deformation, shape programming, and moderately large actuation forces when driven by an external magnetic field. These capabilities enable applications such as soft grippers, biomedical devices, and actuators. To facilitate complex shape deformation and enhanced range of motion, a unimorph can be designed with varying geometries, behave spatially varying multi-material properties, and be actuated with a non-uniform external magnetic field. To predict actuation performance under these complex conditions, an analytical model of a segmented MAE unimorph is developed based on beam theory with large deformation. The effect of the spatially-varying magnetic field is approximated using a segment-wise effective torque. The model accommodates spatially varying concentrations of magnetic particles and differentiates between the actuation mechanisms of hard and soft magnetic particles by accommodating different assumptions concerning the magnitude and direction of induced magnetization under a magnetic field. To validate the accuracy of the model predictions, four case studies are considered with various magnetic particles and matrix materials. Actuation performance is measured experimentally to validate the model for the case studies. The results show good agreement between experimental measurements and model predictions. A further parametric study is conducted to investigate the effects of the magnetic properties of particles and external magnetic fields on the free deflection. In addition, complex shape programming of the unimorph actuator is demonstrated by locally altering the geometric and material properties.

Original languageEnglish (US)
Article number095021
JournalSmart Materials and Structures
Volume32
Issue number9
DOIs
StatePublished - Sep 2023

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Civil and Structural Engineering
  • Atomic and Molecular Physics, and Optics
  • General Materials Science
  • Condensed Matter Physics
  • Mechanics of Materials
  • Electrical and Electronic Engineering

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