Near infrared-induced shape memory polymer composites with dopamine-modified multiwall carbon nanotubes via 3D-printing

Abstract

A simple modification process was developed to improve the mechanical and thermal properties of near-infrared (NIR) induced shape memory polymer composites without compromising their shape memory properties. A combination of 3D printing technology and polyurethane/polycaprolactone blends with dopamine/multi-walled carbon nanotubes (PMWCNTs) filler was used in preparing NIR-induced shape memory composites. The X-ray photoelectron spectroscopy, Fourier transformed infrared (FTIR), thermo gravimetric analysis (TGA), and transmission electron microscopy imaging results showed that the MWCNTs were successfully modified. The tensile strength of composites reached 46.1 MPa when PMWCNTs content was 3 wt%. The scanning electron microscopy imaging results revealed a good dispersibility of PMWCNTs in composites. FTIR results showed that PMWCNTs formed hydrogen bonds with composites matrix. The X-ray diffraction (XRD), TGA, and Differential scanning calorimetry results illustrated that PMWCNTs were beneficial for improving the crystallinity and thermal properties of composites, further proving the existence of hydrogen bonds. The addition of PMWCNTs made composites to have higher thermal conductivity. The high thermal conductivity of 1.901 W m−1 K−1 was achieved at a relatively low content of PMWCNTs (5 wt%), which was 3.6 times higher than that of the composites without fillers. When the PMWCNTs’ content was 3 wt%, the composites still showed that the shape fixity rate was over 90% and the shape recovery rate was over 75% after three shape memory cycles, indicating that the good shape memory property was retained. The shape memory behavior of NIR induced 3D printed models was successfully achieved and is obviously demonstrated.