Polymer composites are widely used as lightweight functional materials for a breadth of applications, including sensors, wearable electronics, and biomedical applications. These materials, however, often suffer from low mechanical strength, particularly at elevated temperatures. Soft hybrid materials with high strength under extreme conditions have been developed at small scales, but to scale these materials up to manufacturing capacities, the fundamental mechanisms of controlling the mechanical behavior of these materials must be understood. This award supports fundamental research to uncover the underlying physics and chemistry that control the high mechanical and functional performance of adaptive polymer nanocomposites. The scientific knowledge resulting from this research has the potential to enable a new class of high-performance materials, and the combined experimental and computational approaches build on an educational paradigm that provides opportunities for students participating in the research, training the next generation workforce in advanced engineering techniques.
A driving motivation of this research is to develop mechanically adaptive materials based on the unique dynamic behavior of nanocomposites. The material system of interest consists of miscible polymers with large differences in glass transition temperature (Tg), coupled with a dispersion of nanoparticles. Spherical nanoparticles adsorbed within a high-Tg polymer and dispersed in a low-Tg polymer matrix have been shown to result in a thermally-induced stiffening behavior. In this research program, the investigators examine the role of chemical and dynamic heterogeneities in particle-polymer interfaces of such polymer nanocomposites to understand the mechanical characteristics of adaptivity. Chemical heterogeneities in interfacial polymer layer are studied to explain the reinforcement phenomena in different polymer architectures and with different particle shapes (nanotubes and nanospheres). Conformation of chains, in looped, stretched, and collapsed states, will be explored via molecular dynamic computational simulations to support the experimental results. Computer simulations are designed to run in parallel with experiments to guide experimental work and to inform material design space. More importantly, the influence of various molecular physical parameters such as chain stiffness can be identified by these simulations. Deformation of polymer nanocomposites under large oscillatory shear will be utilized to reveal the fundamental mechanism of adaptive mechanics in composites. Existing network theories will be used to analyze the non-linear rheological data and the effects of different polymer architectures on particle behavior. The knowledge gained from this project will transform the current knowledge of static properties of nanocomposites to extend to dynamically adaptive polymer hybrids.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
