NSF Award
0521771
This grant provides funding for a study in which new modeling strategies will be implemented to predict orientation development during injection molding of thermotropic liquid crystalline polymers (TLCPs). The excellent properties of TLCPs are intimately linked to the spontaneous ordering of rodlike molecules in the nematic liquid crystalline phase, and the subsequent impact of processing on the molecular orientation state. Prediction and control over the evolution of molecular orientation during processing is a prerequisite for optimized fabrication of TLCP moldings. The modeling will exploit a so-called 'polydomain' description of orientation which facilitates direct comparisons to experimental data. This effort is exploits a close analogy with fiber orientation models used in composite process modeling. The computational program will be coordinated with cutting edge synchrotron experiments to quantify molecular orientation: (i) in situ x-ray scattering measurements of orientation in real time during the injection molding cycle, and (ii) a novel ex situ synchrotron spectroscopy technique that offers unprecedented 3-D characterization of the molecular orientation distribution within the surface layer of moldings.<br/><br/>This project will have broad impact in technology, scientific infrastructure, and human resources. Improved insights into orientation development in TLCP processing, as well as development and critical evaluation of predictive modeling tools, should favorably impact the technological application of these materials. The broader scientific community will be served by development of a new apparatus for in situ studies of polymer injection molding. Students assigned to this project will learn cutting-edge experimental and modeling tools. Finally, the outreach efforts will engage undergraduate students, teachers and faculty from 4-year universities in the project, and exploit Michigan Molecular Institute's unique position to disseminate the methods and results of this project to industry.
