This Faculty Early Career Development (CAREER) award supports fundamental research to deliver essential knowledge that will significantly improve the predictive modeling of the injection molding process for engineering plastics. Modern technical applications demand plastic components that can withstand extreme conditions, display critical dimensional stability or undergo predictable biodegradation. It is well known that these important properties can be significantly affected by manufacturing conditions. To ensure the production of a robust component, simulation models are used to optimize processing. However, current simulations cannot accurately predict the properties of a plastic component created during manufacturing. As a result, time-consuming and expensive trials are needed to prepare for manufacturing. Improving these process models requires new knowledge in the field of polymer crystallization that will be delivered through this interdisciplinary research program. Improved simulation models will reduce lead time in domestic manufacturing processes, resulting in benefits for the U.S. economy and society. The program is designed for rapid dissemination of results into the industrial community, and underrepresented groups engaged herein are provided the opportunity to develop technical skills while interfacing with both academic and industrial scientists.
This award supports the first known effort to establish the cooling-rate dependence of shear induced crystallization kinetics, an important missing link required to model polymer flow and solidification. Through a novel combination of rheological and ultra-fast calorimetric techniques, the research will establish the crystallization kinetics that result from crystalline precursors formed under shear. Ultrafast calorimetry will accurately mimic the thermal conditions under which injection molded polymer microstructures are formed. The resulting critical kinetic data will be used to develop the fundamental understanding that will enable improvements in current crystallization models, while the accurate material-specific data will drive these models. The research will establish the crystallization behavior of flow-induced precursors without forfeiting the process history of the melt, a loss that cannot be avoided using conventional research methods that are three orders of magnitude too slow to suppress the extremely rapid polymer reorganization. Through collaborative efforts, resulting models will be incorporated into commercial polymer flow simulation software, which will provide a much more robust model for manufacturing process simulation than is currently available.
|Effective start/end date
|2/1/17 → 1/31/23
- National Science Foundation: $661,777.00