3D-printable stimuli-responsive covalent adaptable networks based on dynamic reversible urea bonds

The current study focusses on three-dimensional (3D)-printing of switchable covalent adaptable networks (CANs), which are based on dynamic urea bonds. Digital light processing (DLP) has been utilized for the printing of 3D structures based on the CANs. Furthermore, CANs have been prepared by bulk polymerization for comparison. All resulting polymer networks were analyzed by various techniques such as mechanical testing (tensile strength, 3-point-flexure, rheology). Furthermore, their self-healing behavior was studied using a quantification via an indentation method. Particular noteworthy is the self-healing ability in complex 3D-printed structures. Finally, the shape-memory behavior was studied in detail. In this context, recovery rates up to 99% could be obtained. The polymers additionally feature excellent mechanical properties with tensile E-moduli between 0.34 GPa up to 3.43 GPa and flexural moduli between 0.52 GPa up to 0.71 GPa.