Dynamic Mechanical Analysis of Magnetorheological Composites

UC Irvine

Lizhi Sun

Problems

The characteristics of magnetorheological materials shows promise for their use in wide applications such as high‐power magnetostrictive actuation for anti‐ vibration applications, magnetoelastic sensor application in civil infrastructures monitoring, and smart on‐demand damping control. Studies of magneto‐mechanical responses for magneto‐ rheological elastomer composites is recently of great interest to researchers and engineers in many science and engineering disciplines with civil infrastructures in particular. While efforts have been made, the inferior mechanical responses of the soft matrix severely inhibit their wide applications.

Approach

To overcome the challenge mentioned above we develop a novel type of magnetorheological (MR) elastomer nanocomposites filled with carbon nanotubes. We further conduct an integrated experimental and modeling approach to investigate the dynamic mechanical behavior of silicone‐rubber‐ based MR nanocomposites enhanced by multi‐walled carbon nanotubes. First, the novel MR nanocomposites have been fabricated, with their microstructures and dynamic viscoelastic properties under applied magnetic fields subsequently characterized via scanning electron microscope and dynamic mechanical analysis. A micromechanics‐based constitutive model is then proposed to predict the dynamic viscoelastic behavior of multi‐phase composites with viscoelastic imperfect interfaces. With the incorporation of the classic dipole‐dipole magnetic interaction model, the scope of the proposed model has been extended to cover as well the magnetic‐field‐induced changes in dynamic stiffness and damping of MR nanocomposites.

Findings

The dynamic mechanical behavior of the MR nanocomposite and MR elastomer under applied magnetic field has been characterized at room temperature, through dynamic single lap‐ shear test with a dynamic mechanical analyzer. The zero‐field storage modulus G' and damping ratio tan δ of MR nanocomposite are at least 30% and 40% higher than those of conventional MR elastomer, respectively, which proves the effective mechanical reinforcement by only 1 wt% of MWNTs in the matrix. The absolute MR effect on G' of MR nanocomposite can reach up to 0.3 MPa, which is almost 70% higher than that of conventional MR elastomer, while the relative MR effect on G' is only around 25% higher since the zero‐field G' is also increased. It is quite possible that a better bonding between iron particles and the matrix has been induced by MWNTs, which leads to the increase in the absolute MR effect. In case of tan δ, the absolute MR effect remains almost unchanged change while the relative MR effect decreases.

Impact

The research conducted is among the first attempt to combine the advantages of nanocomposites and magnetostrictive materials to produce the novel MR nanocomposites. The work is expected to lead to advances in the development of smart nano‐ composites in applications such as smart valves, smart wings, adaptive vibration control and noise reduction, and non‐contact position sensors.

Core Competencies

  • Nanomechanics of composites.
  • Multiscale materials modeling.
  • Dynamic mechanical analysis of polymers and composites.
  • Development and characterization of smart nanocomposites.

Current Research Team Members:

  • Lizhi Sun (PI)
  • Yu Wang (Ph.D. Candidate)
  • Yongxue Li (Ph.D. Candidate)
  • Robbie Damiani (Graduate Student)
  • Hesam Sajed (Graduate Student)
  • Hui Wang (Visiting Scholar)

Recent graduates and co‐workers

  • Huiming Yin (PhD), Assistant Professor, Columbia University.
  • Hua Liu (PhD), Civil Engineer.
  • Rui Li (PhD), Civil Engineer.

Current research collaborations

  • Multiscale modeling of Fe‐Ga magneto‐strictive alloys ‐ R. Wu (Physics, UC Irvine), Z.D. Zhang (Chinese Academy of Sciences, China)
  • Development and modeling of magneto‐strictive nanocomposites ‐ Y. Huang (Northwestern University)
  • Nano‐CT‐based elastography of hetero‐geneous materials ‐ L. Valdevit and T. Rupert (MAE, UC Irvine), G. Wang (Virginia Tech).