Micromechanism-based magneto-thermomechanical properties of magnetic particles filled shape memory polymer composite

Magnetic nanoparticles-filled shape memory polymer composite (MSMPC) possesses excellent magnetothermal property, showing wide prospects for engineering applications. The thermo-magnetically triggered shape memory (SM) process contains complex multi-physical mechanisms, especially when coupled with finite deformation rooted on micro-mechanisms. A multi-physicals finite deformation model is necessary to get a deep understanding on the coupled magneto-thermo-mechanical properties of MSMPC, beneficial to its design and wide application. Taking into consideration of micro-physical mechanisms of the nanoparticles interacting with chain network, a finite deformation theoretical model is developed in this work based on two superimposed networks of a crosslinked network formed between magnetic particles (PP network) and another crosslinked network of polymer chains (CC network). The intact CC network is considered featuring with entropic-hyperelastic properties, superimposed with a PP network where effects of particle size and chain distribution between particle-pairs are considered. The model is calibrated by a series of experiments and is further used to investigate multiply (magnetically and thermally) triggered shape recoveries by directly heating and magnetic-heating due to Neel and Brown relaxation. Numerical examples assess the effects of nanoparticle concentration and size, magnetic field strength, loading strain rate and phase evolution on SM behavior. This model demonstrates good feasibility in capturing the coupled magneto-thermo-mechanical behavior of MSMPC and provides theoretical understandings and design guidelines for MSMPC.