NSF-DFG: Multiscale Data-Physics Models for the Critical Role of Interfaces in Overmolded Thermoplastic Parts

该奖项支持与连接两个不同聚合物层相关的美德合作研究。聚合物超塑技术被应用于汽车、航空、能源和生物医学等领域的众多工业制造过程中。只有在两个不同的部件之间有良好的粘附性，这些复合材料才能实现其所需的性能，并避免部件故障或过度设计。目前，这是通过使用简单的特别模型和反复试验的做法来实现的。详细的模型和理解还没有形成，因为有多个空间和时间尺度以及控制制造部件行为的过程形态参数。各种分子过程的影响，以及每个过程/形态参数的作用，以及它们对所制造的部件的综合影响，目前还不是很清楚。该奖项将支持基础研究，通过将界面属性与发生在这些关键界面上的分子过程联系起来，帮助了解粘结强度和断裂韧性。行业合作者将帮助确保新知识和计算工具的实际应用。综合计算材料工程范式将通过培训下一代工程师和科学家在产品、组成产品的材料、相关材料加工方法和多尺度建模方面得到提升。为了解决热塑性塑料覆盖件界面失效的基本问题，该项目将采用新颖的多尺度计算建模，结合不断发展的机器学习工具，以定量了解影响粘合强度和断裂韧性的因素。特别是，该项目将：(I)发展分子水平的理解，以定量地预测层压板/半结晶聚合物界面的强度和断裂韧性随工艺参数的时间演变；(Ii)将这些信息与粗粒度积分器相结合，以预测并优化界面属性；以及(Iii)为这些复合材料的集成制造和产品设计一个经过验证的混合数据-物理驱动的多尺度框架。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award supports US-German collaborative research related to joining two dissimilar polymer layers. The polymer overmolding technique is employed in numerous industrial manufacturing processes, in application areas including automotive, aeronautics, energy, and biomedicine. These composite materials can achieve their desired properties and avoid part failure or overdesign only if there is good adhesion at the interface between the two disparate components. Currently this is achieved through the use of simple ad hoc models and trial-and-error practices. Detailed models and understanding have not yet been formed because there are multiple spatial and temporal scales and process-morphology parameters that govern manufactured part behavior. The effect of various molecular processes and the role of each of the process/morphology parameters and their combined effect on the manufactured component is not well understood today. This award will support fundamental research to help understand the bonding strength and fracture toughness, by relating interface properties to molecular processes taking place at these critical interfaces. Industrial collaborators will help ensure the practical application of the new knowledge and computational tools. The Integrated Computational Materials Engineering paradigm will be advanced by educating the next generation of engineers and scientists in integrated design of products, the materials that comprise them, their associated materials processing methods, and multiscale modeling.To address the fundamental issue of interface failure in overmolded thermoplastic parts, this project will employ novel multiscale computational modeling, coupled to the evolving tools of machine learning, to quantitatively understand the factors that affect adhesion strength and fracture toughness. In particular, this project will: (i) develop a molecular-level understanding to quantitatively predict the temporal evolution of the strength and fracture toughness of a laminate/semicrystalline polymer interface as a function of process parameters; (ii) combine this information with a coarser-grained integrator to predict and hence optimize interface properties; and (iii) design a validated hybrid data-physics driven multiscale framework for integrated manufacturing and product design of these composites.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.