Impact of shape-memory programming on mechanically-driven recovery in polymers

Abstract

Shape-memory polymers (SMPs) are a class of mechanically functional “smart” materials defined by their ability to change shape upon exposure to an environmental stimulus. The shape-memory effect has traditionally been activated by thermal mechanisms via heating the polymer above a transition temperature to increase chain mobility and initiate shape recovery. This study proposes a unique approach to mechanically drive recovery in SMP networks using external forces to facilitate shape change in a material with stored strain. SMP networks were synthesized from tert-butyl acrylate and poly(ethylene glycol) dimethacrylate in three network compositions. Networks were tailored to maintain a constant glass transition temperature (∼52 °C) with increasing crosslinking density, shown by rubbery modulus values of 1.2, 3.1, and 8.2 MPa. Hollow SMP cylinders were axially elongated (programmed) to stored strain levels of approximately 25%. A second set of samples was machined to match the programmed dimensions of the SMP sample set. Compression testing revealed that the compressive strength and energy required for deformation for the programmed SMP samples were on average 62% and 52% of the as-machined samples’ values, respectively. The ratios between programmed and as-machined samples’ compressive properties were independent of both crosslinking density and temperature up to the onset of glass transition. Lastly, an interference-fit test model was used to demonstrate that mechanically-driven SMPs could immediately create and maintain a stronger fixation force compared to as-machined samples and thermally-driven SMP samples. This study introduces an approach to drive shape change that mitigates the time-temperature dependence and discusses the potential of this mechanism for biomedical devices.