This dissertation work focuses on the thermomechanical behaviors of two recent exciting developments in active polymers: shape memory (SM) effects and covalent adaptive network polymers with bond exchange reactions. Both polymers are active in performing prescribed functions when an external stimulus is applied. The goals of the studies are to understand complex thermomechanical behaviors of such smart polymers through experiments, develop constitutive models to describe the behaviors, and use the developed models to assist their development and engineering applications. For the polymer SM effect, we use a multi-branched constitutive model to study the SM effect achieved by polymer glass transition. The major finding of our study is that the “Reduced Time” is identified to be the unique parameter to determine the polymer shape fixity and recovery ratio under different thermo-temporal conditions in an SM cycle. Based on the theoretical knowledge, we also study the energy releasing mechanism within shape memory polymers (SMPs), multi-shape memory effects, as well as the SM properties in various composite systems, such as magnetic particles, carbon black and microvascular reinforced SMP composites. For the covalent adaptive network polymers, we adopt the emerging covalent chemistry BERs to achieve a malleable, reparable, recyclable and yet insoluble thermoset network. After being pulverized into micro-size, and then compressed either at high temperature or just facilitated by the moisture, the polymer powder could be welded on the interfaces, and assembled together into a new sample with comparable mechanical properties to the fresh sample. Theoretical models are developed to gain fundamental understanding of how the processing conditions can affect the quality of reprocessed materials. A molecular model is developed to understand welding kinetics at the interface. Such understanding is then used to develop a multiple length scale interfacial constitutive model, which can be implemented in to finite element simulation software to assist computational study of reprocessing process.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/53896 |
| Date | 21 September 2015 |
| Creators | Yu, Kai |
| Contributors | Qi, H. Jerry |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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