DMREF/Collaborative Research: Integrated Material Design and Processing--Application to Recycled Plastics

DMREF/合作研究：集成材料设计和加工——在再生塑料中的应用

• 批准号: 2119040
• 负责人: Thao Nguyen
• 金额: $ 108万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-12-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2119040&HistoricalAwards=false
• 关键词: DMREF; Collaborative; Research; Integrated; Material

Materials manufacturing is subject to uncertainty in raw materials and processes that can drastically alter the resulting properties. Defects can lead to costly re-tuning of the process recipes and prevent production of certified products. To address these challenges, this Designing Materials to Revolutionize and Engineer our Future (DMREF) award will support the development of a data-centric approach for integrated materials design and manufacturing, called Materials Architected by Adaptive Processing (MAAP). In this approach, the same data and data infrastructure applied for materials design will be harnessed for process monitoring and control to ensure consistent production of materials with targeted properties. As a specific example, the MAAP approach will be used to design and produce polymer blends with superior properties from recycled material. The award will also advance fundamental understanding of mixing and flow-induced crystallization in multi-polymer melts and apply that understanding to produce architected blends from recycled polymers. The ability to upcycle plastic waste will improve sustainability and reduce the environmental impact of plastics production. The project will contribute to the workforce development by: 1) developing student projects that integrate data science, experimentation, and computation; 2) providing research internships for high-school students traditionally underrepresented in engineering; and 3) offering training for practicing engineers, technicians, and managers in recycling, melt blending, and quality control.The goal of this project is to develop the integrative MAAP approach to make the materials-by-design process more robust and provide adaptive processing systems for consistent materials production. This goal will be pursued in the context of superior polymer blends obtained from recycled polyethylene and isotactic polypropylene. The approach involves five key interrelated tasks. An event-driven, microservices data layer will automate the contextualized data flow between the processing, characterization, multiscale modeling, decision, and control tasks of the project. An instrumented co-extrusion process with modular shape-multiplying elements will be designed based on the modeling studies to investigate the controllability of the melt streams and observability of the architected blends. Micro-scale modeling of flow-induced crystallization (FIC) of the multi-polymer melt system will study the effects of the domain interfaces and processing conditions on the development of crystalline morphologies and provide material models of FIC for meso-scale studies. Meso-scale models will investigate the stability of the melt streams through the shape-multiplying elements and the formation of phase domains during processing to determine how the measurable processing parameters control the crystalline morphologies and domain architecture. Materials characterization and micromechanical modeling will investigate the effect of the crystalline and domain structures on the mechanical properties of the architected blends.This project is co-funded by the Division of Civil, Mechanical and Manufacturing Innovation in the Directorate for Engineering and the Division of Materials Research in the Directorate for Mathematical and Physical Sciences.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.

材料制造受到原材料和工艺的不确定性的影响，这些不确定性可能会极大地改变所产生的性能。缺陷可能导致重新调整工艺配方的成本高昂，并阻止生产经过认证的产品。为了应对这些挑战，DMREF设计材料奖将支持开发一种以数据为中心的集成材料设计和制造方法，称为自适应处理(MAAP)材料架构。在这种方法中，应用于材料设计的相同数据和数据基础设施将被用于过程监测和控制，以确保一致地生产具有目标性能的材料。作为一个具体的例子，MAAP方法将被用于从回收材料中设计和生产具有优异性能的聚合物共混物。该奖项还将促进对多聚合物熔体中混合和流动诱导结晶的基本理解，并将这一理解应用于从回收聚合物中生产设计的混合物。回收塑料垃圾的能力将提高可持续性，并减少塑料生产对环境的影响。该项目将通过以下方式促进劳动力发展：1)开发整合数据科学、实验和计算的学生项目；2)为传统上在工程学中代表性较低的高中生提供研究实习；以及3)为实习工程师、技术人员和管理人员提供回收、熔融混合和质量控制方面的培训。该项目的目标是开发综合的MAAP方法，使按设计设计的材料过程更加稳健，并为一致的材料生产提供自适应的加工系统。这一目标将在从回收聚乙烯和等规聚丙烯获得的优质聚合物共混物的背景下进行。该方法涉及五项相互关联的关键任务。事件驱动的微服务数据层将使项目的处理、表征、多尺度建模、决策和控制任务之间的上下文数据流自动化。在模型研究的基础上，设计了一种带有模块化倍形元件的仪表化共挤出过程，以考察熔体流动的可控性和设计的共混物的可观测性。聚合物熔体体系流动诱导结晶(FIC)的微观模拟将研究微区界面和加工条件对结晶形态发展的影响，并为细观尺度的研究提供材料模型。细观模型将通过形状倍增元件研究熔体流动的稳定性和加工过程中相区的形成，以确定可测量的加工参数如何控制晶体形态和相区结构。材料表征和微观机械建模将调查晶体结构和区域结构对建筑混合体机械性能的影响。该项目由工程局的土木、机械和制造创新部和数学和物理科学局的材料研究部共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。