GOALI: Shape Memory Polymer Composites

Syracuse University, Syracuse NY

Investigators

Abstract

TECHNICAL: A university-industry collaboration is established to address outstanding questions concerning the limitations of current polymer-based shape memory technology by studying new composite systems capable of both shape memory behavior and improved physical properties. Here, shape memory is the process whereby a material that has been deformed and temporarily fixed in this deformed shape can be triggered to recover to its original, un-deformed, permanent shape. Such a phenomenon can be exploited for actuation and device deployment. For high performance applications, high thermal and electrical conductivity, high stiffness, and outstanding durability are needed. In this collaborative research project, a composite approach is adopted to meet these needs. Unique materials design, processing and thermo-mechanical characterization (SU) is combined with detailed microstructural and interface characterization (GM) that will lead to quantitative and mechanistic understanding that connects material composition, and reinforcement/matrix physical and chemical interactions with the composites bulk properties and their shape memory performances. Design guidelines will be established for developing new shape memory polymer composites (SMPCs) with improved properties and performances that will offer new solutions for structural applications. By comparing multiple materials systems consisting of the same matrix composition but with varying reinforcement types, the effects of reinforcement/matrix-specific interactions on the composites bulk properties will be determined. NON-TECHNICAL: ?Smart? materials offer the potential to greatly simplify mechanical designs utilized in diverse fields of manufacturing, mechanical devices, robotics, and packaging to name a few. This is possible because unlike conventional motors, the material of construction, itself, changes shape during actuation. The focus of this research project is on a particularly exciting class of smart materials, namely shape memory polymers, SMPs. Despite the promise of SMPs, their mechanical and actuation properties have thus far been limited relative to the requirements of demanding applications mentioned above. In this research, the university-industry team will significantly increase the properties of existing and scalable SMPs using a variety of reinforcement strategies. The research activities and outcomes will broadly impact researchers in the fields of materials science and engineering by revealing new processing and design tools and fundamental understanding of composite properties, herein applied to shape memory but broadly applicable to other properties and applications. By integrating the proposed research and education, graduate and undergraduate students will have the opportunity to participate in research activities within the fast-paced industrial setting on a problem with significant industrial relevance and high impact potential for innovation. In addition, the findings resulting from the proposed research will be translated in the classroom by the PI. In particular, design tools for shape memory polymers will be developed by undergraduate student teams and applied to several real world applications, including medical devices, household goods, and mechanical mechanisms. Simultaneously, the resulting design tools will provide the materials field at large with a much-needed database of the inter-relationships between properties, design, and shape memory figures-of-merit for SMPCs.