Thesis Topic
Tuning the Processability of Thermal Stimuli-Responsive Lightly Crosslinked Liquid Crystalline Epoxy Networks
Thesis
Liquid crystal epoxy networks (LCEN) are a novel branch of materials with many unique capabilities, such as shape memory and self-healing, which lend well to smart devices, sensors, actuators, and adaptive coatings. Significant challenges in the processing of these materials should be overcome to enable wider adoption of functional liquid crystal epoxies. Among these challenges are the rheological complexity of epoxy curing that can make the material difficult to 3D print, the inability of crosslinked epoxy to be recycled, and the undefined influences that processing conditions and chemistry have on the formation of functional liquid crystal domains. To address these challenges, several strategies are discussed and explored. First, printability criteria for uncured LCEN are established through rheological characterization of high and low shear environments. Second, recyclability of functional LCEN is introduced by way of catalyzed dynamic covalent bonding. This mechanism of self-healing leaves the crosslink density of the LCEN unaffected, so the functional capabilities of shape memory are hypothesized to be unaffected. Thirdly, the exact effects of curing agent selection as a means of tuning the functional capabilities of LCEN are demonstrated by modulating the volume fraction of liquid crystal domains in the LCEN.
Biography
I’m a PhD student in Materials Science and Engineering, where I also completed my undergrade degree. Over the past few years, I’ve had the opportunity to design and lead instructional undergraduate laboratories and I have quickly discovered a passion for teaching from these experiences. The majority of my research experience is in the field of rheology, originally working with bituminous tack coatings. I’ve served as a rheological consultant for many different projects, having designed novel experiments for measuring thermal expansion, phase stability for phase change materials, and shape memory behavior of liquid crystal epoxy networks.