Abstract
Nanocomposites based on a shape memory polymer matrix are emerging smart materials of great application potential due to their high deformability and good shape memory performance as well as decent mechanical properties. In the paper, a detailed theoretical study on the thermoviscoelastic behaviors and shape memory effects of multiwall carbon nanotubes (MWCNT) reinforced epoxy nanocomposites is presented. Different from the traditional shape memory cycle procedure, both the loading and memory processes in the study are programmed below the glass transition temperature, which is so-called cold deformation. A novel network transition constitutive model incorporated with a micro-mechanics model to determine the effective properties of the nanocomposites is proposed to study the underlying stress relaxation and shape memory mechanisms. The involved parameters are determined from standard thermomechanical experiments. Then we implement the model into Mathematica to predict the thermomechanical behaviors of both the neat and filled shape memory polymers subjected to different programming conditions, and the simulation results show good agreement with the experimental results. Moreover, the shape memory properties of the material as well as the influence of MWCNT on the material behavior are discussed in detail.
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