Abstract
Abstract
Two-way shape memory polymers are stimulus-responsive materials capable of changing their shape between two configurations based on an on/off thermal stimulus. While the traditional effect has been studied under the application of an external mechanical load, it was demonstrated also in the absence of an external load. Such a response only relies on a carefully tailored macromolecular architecture of the polymer combined with a specific thermo-mechanical protocol. In particular, semicrystalline networks, either consisting of a multi-phase copolymer network or a homopolymer based network with broad phase transitions, have been proposed to this aim under ad hoc thermo-mechanical histories. In this work, the two-way shape memory behavior is studied on a poly(ϵ-caprolactone)-based network, crosslinked by means of a sol–gel approach and tailored on the selection of the molecular weight of the precursor polymer. Changing the prepolymer precursor allowed to tune the melting/crystallization regions of the networks, thus the thermal region of the reversible shape memory effect. The application of properly designed thermo-mechanical cycles allowed to study the two-way shape memory effect without the application of an external load under tensile conditions. Given a specific network, the stress-free actuation of the reversible elongation-contraction cycle under tensile conditions was induced across its specific melting/crystallization region. The extent of the effect was found to depend on the crystalline fraction remaining for the given actuation temperature and on the tensile stretched state imposed on the materials during the training step. The results were compared with the response achieved under the traditional two-way shape memory protocol under stress. The stress-free two-way shape memory effect was also successfully demonstrated and emphasized, under flexural conditions, which suggests the potential of these materials as intrinsically reversible actuators, promising for applications in the biomedical field and/or for soft robotics.