Self-healing polymers (SHPs) are a type of stimuli responsive material that can mend mechanical damages with little to no external intervention. One approach to achieve self-healing is by introducing a low melting temperature thermoplastic healing agent that diffuses across cracks and defects to facilitate healing. Research into the 3D printing of these stimuli responsive materials has increased due to the need for functional complex geometries of high resolution. However, there is a lack of understanding with respect to how the interplay of 3D printing parameters and material composition influences the properties of such materials, including their self-healing behavior. In this work we will examine the role that LCD 3D printing parameters, such as layer height and temperature, have on the healing efficiency of extrinsic 3D printed SHPs. Material compositions are based on 2-phenoxyethyl acrylate (POEA) and 1,6-hexanediol dimethacrylate (HDDMA) with varying concentrations of polycaprolactone (PCL), which acts as the extrinsic healing agent. After mixing at 80°C for an hour, the POEA monomer and melted PCL remains a homogenous mixture at room temperature for concentrations up to 40wt% PCL. However, polymerization induced phase separation occurs following irradiation which results in an incompatible polymer blend. This is indicated by an insensitivity of the glass transition to PCL concentration and an increase in enthalpy of melting that scales with PCL content. Upon heating, the presence of the thermosetting network enables shape retention while PCL melts and flows during healing. When cooled, the PCL solidifies and partially restores the mechanical strength of the part. Interestingly, the self-healing efficiency differed according to printed layer thickness. For example, a tensile bar with 20wt% PCL printed with 100mm layers showed 89% recovery of ultimate elongation as compared to the same part printed with 10mm layers that showed only 32% recovery. These results show a definitive difference in self-healing properties as a function of 3D printing parameters and this concept will be further discussed in this poster presentation.

Structure-property-processing relationship of 3D printable self-healing polymer blends

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