CAREER: Flow-Induced Crystallization for Advanced Plastics Engineering

该学院早期职业发展（Career）奖支持基础研究，提供必要的知识，这些知识将显著改善工程塑料注射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经历可预测的生物降解。众所周知，这些重要的性能会受到制造条件的显著影响。为了保证生产出具有鲁棒性的零件，采用仿真模型对加工过程进行优化。然而，目前的模拟不能准确地预测制造过程中产生的塑料部件的性能。因此，为了准备生产，需要进行耗时且昂贵的试验。改进这些过程模型需要聚合物结晶领域的新知识，这些知识将通过这个跨学科的研究项目提供。改进的仿真模型将减少国内制造过程的交货时间，从而为美国经济和社会带来好处。该计划旨在将结果快速传播到工业界，并为参与其中的代表性不足的群体提供了发展技术技能的机会，同时与学术和工业科学家进行交流。该奖项支持了已知的首次建立剪切诱导结晶动力学的冷却速率依赖性的努力，这是模拟聚合物流动和凝固所需的一个重要缺失环节。通过一种新颖的流变学和超快速量热技术的结合，该研究将建立在剪切作用下形成的结晶前体的结晶动力学。超快量热法将准确地模拟注塑成型聚合物微观结构形成的热条件。由此产生的关键动力学数据将用于发展基本的理解，从而改进当前的结晶模型，而准确的材料特定数据将推动这些模型。该研究将建立流动诱导前体的结晶行为，而不会丧失熔体的过程历史，这是传统研究方法无法避免的损失，因为传统研究方法速度太慢，无法抑制极其快速的聚合物重组。通过共同努力，得到的模型将被整合到商用聚合物流动模拟软件中，这将为制造过程模拟提供比目前可用的更强大的模型。

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.