Microscopic double-chain sawtooth model and macroscopic four-parameter fractional-order derivative viscoelastic model based on magnetorheological elastomers

In order to restore the distribution of ferromagnetic particles in magneto-rheological elastomers to the greatest extent, the magnetotropic effect of magneto-rheological elastomers is more accurately represented, and the dynamic mechanical properties of magneto-rheological elastomers are more accurately reflected. In this paper, based on the dipole theory, a new microscopic model of magnetorheological elastomer, the double chain sawtooth model, is proposed based on the chain model and the main chain adsorption model, and a macroscopic viscoelastic mechanical model of magnetorheological elastomer, the four-parameter fractional order derivative improvement model, is proposed based on the classical macroscopic mechanical parametric model and the fractional order derivative model. A microscopic model of magnetorheological elastomer was combined with a macroscopic model to describe its mechanical properties. Isotropic and anisotropic magnetorheological elasto-mers with different mass fractions and different silicone oil contents were prepared using silicone rubber as the matrix and carbonyl iron powder as the filling phase, and dynamic shear tests were conducted to verify the validity of the model.

Automated summary

In order to accurately represent the magnetotropic effect and dynamic mechanical properties of magneto-rheological elastomers, a new microscopic model called the double chain sawtooth model was proposed based on the dipole theory. Additionally, a macroscopic viscoelastic mechanical model known as the four-parameter fractional order derivative improvement model was proposed to combine the microscopic and macroscopic models and describe the mechanical properties of magneto-rheological elastomers. Experimental tests were conducted on isotropic and anisotropic magneto-rheological elastomers with different mass fractions and silicone oil contents to validate the proposed models.