Numerical investigation of smart auxetic three-dimensional meta-structures based on shape memory polymers via topology optimization

Today, the human being endeavors to manufacture devices and materials capable of doing something in an intelligent way. Shape memory polymers are a series of smart materials, capable of retrieving their original shape from a temporary form by applying external stimuli, for example, heat, electricity, magnetism, light, pH, and humidity. In this research, the behavior of temperature-sensitive shape memory polymer–based structures with positive and negative Poisson’s ratio has been analyzed. The purpose is the material design of smart structures with tunable Poisson’s ratio using topology optimization. In this study, a meta-structure is designed, which is made by a smart material. Not only does this structure have shape memory effects, but also it has negative Poisson’s ratio, which can be used in new sensors, actuators, and biomedical applications. After creation of the unit cell and the representative volume element and formation of final three-dimensional structure, finite element modeling is conducted based on a thermo-visco-hyperelastic constitutive model at large deformations. Examining the behavior of structures in tensile pre-strains of 20%, 10%, and 5%, it is observed that pre-strain has no considerable effect on Poisson’s ratio, but under compressive strain of 20%, it is concluded that the type of loading is effective on Poisson’s ratio and the results are different in tension and compression modes. Finally, the influence of temperature rate on the behavior of structures is inspected, and it is concluded that the more slowly the temperature changes, the more strain or shape recovery is accomplished at a specific temperature.