CAREER: Flow-Induced Crystallization for Advanced Plastics Engineering

这个教师早期职业发展（CAREER）奖支持基础研究，以提供基本知识，这将显着提高工程塑料注塑成型过程的预测建模。现代技术应用要求塑料部件能够承受极端条件，显示临界尺寸稳定性或进行可预测的生物降解。众所周知，这些重要的性能会受到制造条件的显著影响。 为了确保生产出坚固耐用的部件，我们使用仿真模型来优化加工。然而，目前的模拟无法准确预测制造过程中产生的塑料部件的特性。 因此，需要进行耗时且昂贵的试验来为制造做准备。 改进这些过程模型需要在聚合物结晶领域的新知识，将通过这个跨学科的研究计划提供。 改进的仿真模型将减少国内制造流程的交货时间，从而为美国经济和社会带来好处。 该计划旨在将成果迅速传播到工业界，并为参与其中的未被充分代表的群体提供发展技术技能的机会，同时与学术和工业科学家进行交流。该奖项支持第一个已知的努力，以建立剪切诱导结晶动力学的冷却速率依赖性，这是一个重要的缺失环节，需要建模聚合物流动和固化。 通过流变学和超快速量热技术的新组合，该研究将建立剪切下形成的结晶前体的结晶动力学。超快量热法将精确地模拟注塑成型聚合物微结构形成的热条件。 由此产生的关键动力学数据将用于发展基本的理解，这将使当前的结晶模型的改进，而准确的材料特定的数据将驱动这些模型。该研究将建立流动诱导前体的结晶行为，而不会丧失熔体的工艺历史，这是使用传统研究方法无法避免的损失，传统研究方法的速度太慢，无法抑制极其快速的聚合物重组。 通过合作，所产生的模型将被纳入商业聚合物流动模拟软件，这将提供一个更强大的模型，制造过程模拟比目前可用的。

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.