Shape-Memory Semicrystalline Polymeric Materials Based on Various Rubbers

A simple strategy is presented for the fabrication of shape-memory materials containing commercial rubbers including natural rubber, cis-polybutadiene, and styrene-butadiene rubber. Dissolution of the rubbers in n-octadecyl acrylate (C18A) monomer followed by UV polymerization at 30 degrees C leads to the formation of interconnected interpenetrating polymer networks (c-IPNs) possessing crystalline domains. They exhibit melting (T-m) and crystallization temperatures (T-cry) between 45-50 and 35-40 degrees C, respectively, that can be tuned by the amount and the type of the rubbers. All c-IPNs exhibit a significant temperature sensitivity in their viscoelastic and mechanical properties when the temperature is changed between below and above T-m and T-cry. The morphology of c-IPNs consists of amorphous nanoparticles of around 64 nm diameter composed of interconnected noncrystalline poly(C18A) (PC18A) and rubber networks, surrounded by crystalline PC18A segments. c-IPNs exhibit tunable mechanical properties, for example, their Young's modulus and toughness can be varied between 8.3-73 MPa, and 1.9-23 MJ center dot m(-3), respectively, by changing the amount and type of the rubber. Because of the coexistence of chemical cross-links and crystalline domains acting as the netpoints and switching segments, respectively, c-IPNs exhibit an efficient shape-memory function as demonstrated by their potential application as a robotic gripper.

Automated summary

This study presents a simple strategy for fabricating shape-memory materials using commercial rubbers. The rubbers are dissolved in a monomer called n-octadecyl acrylate (C18A) and then polymerized using UV light to form interconnected interpenetrating polymer networks (c-IPNs) with crystalline domains. The resulting materials exhibit tunable melting and crystallization temperatures, as well as adjustable mechanical properties. The coexistence of chemical cross-links and crystalline domains allows the c-IPNs to efficiently demonstrate shape-memory functionality.