Self-Folding Shape-Memory Elastomer Composites with Controlled Topographies

Shape-memory elastomer composites (SMECs) are materials able to recover their as-processed shape stored in an elastomer matrix, from another highly deformed shape, stored thanks to a fibrous reinforcement e.g. semi-crystalline. The initial shape is recovered by the melting of the fibers, releasing the applied stress on the matrix. This work aims at presenting an innovative one-step process to achieve a SMEC of electrospun poly(ε-caprolactone) (PCL) fibers, embedded in an elastomeric poly(dimethyl siloxane) (PDMS) matrix. Remarkably, the developed process based on the specific impregnation of a honeycomb structured PCL electrospun fiber mat by liquid PDMS precursor leads after crosslinking to SMEC sheets able to fold on themselves upon mono-axial traction. This is due to the structuration of the composite as a bilayer due to different affinities between the polymers. The amplitude and direction of self-folding can be controlled by the applied strain and by the orientation of the uniaxial tension towards the honeycomb structure. Folding was quantified following a specially adapted dynamic mechanical analysis (DMA) protocol. The advantage of such honey-comb structured SMEC relies in getting a large scope of curves depending on its elongation direction because additionally to bending, shear or torsion modes can be turned on or off. Importantly, whatever the geometry, the shape-memory cycles were found highly reproducible.<br/> As compared to reported works on self-folding SMEC bilayers [1], the one-step process developed here prevents possible delamination, and allows reducing the final material thickness. In addition, these structured SMEC sheets exhibit a smooth side that becomes located at the interior of the self-curved shape while the external side presents a regular rugosity pattern. This particular feature makes these self-folding SMECs particularly interesting in the cardiovascular field, for the elaboration of implants such as stents.<br/><br/><br/>[1] J.M. Robertson, A.H. Torbati, E.D. Rodriguez, Y. Mao, R.M. Baker, H.J. Qi, P.T. Mather <i>Soft Matter </i><b>2015</b>, <i>11(28)</i>, 5754.