Ternary Composite for Controlled Shape Memory Transformations
Sprache des Vortragstitels:
IEEE Sensors 2019
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In this contribution we present an approach towards programmable shape memory transformations utilizing the intrinsic physical properties of a ternary polymer-based composite. The underlying idea is to use an open porous elastic skeleton as the base, where the pores are filled with a component that can alter its elasticity abruptly upon an external stimulus. In this study we use PDMS as the base network, and Paraffin as the pore filler, which causes a huge change in elasticity of the composite when undergoing the solid to liquid phase change at elevated temperature. This binary composite, already featuring shape memory characteristics, is then additionally made controllable by adding nano-particles with specific stimulus responsive properties. We demonstrate the programmable shape transformation capability of the devised ternary composite by the example of carbon black and ferromagnetic iron oxide nano ?