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: 2118769
• 负责人: Peter Olmsted
• 金额: $ 36万
• 依托单位: Georgetown 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=2118769&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影响，这些不确定性可能会极大地改变最终的性能。缺陷可能导致成本高昂的工艺配方重新调整，并阻止生产经过认证的产品。为了应对这些挑战，“设计材料以彻底改变和设计我们的未来”(DMREF) 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“自适应处理架构材料”(MAAP)。在这种方法中，用于材料设计的相同数据和数据基础设施将用于过程监控和控制，以确保一致地生产具有目标特性的材料。作为一个具体示例，MAAP 方法将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元聚合物熔体中的混合和流动诱导结晶的基本理解，并将这种理解应用于从回收聚合物生产结构化共混物。回收塑料废物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）为传统上工程领域代表性不足的高中生提供研究实习机会； 3) 为执业工程师、技术人员和管理人员提供回收、熔体共混和质量控制方面的培训。该项目的目标是开发综合 MAAP 方法，使材料设计过程更加稳健并提供适应性加工一致的材料生产系统。这一目标将在由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实现。该方法涉及五个关键的相互关联的任务。事件驱动的微服务数据层将自动化项目的处理、表征、多尺度建模、决策和控制任务之间的上下文数据流。将根据建模研究设计具有模块化形状倍增元件的仪表化共挤出工艺，以研究熔体流的可控性和设计共混物的可观察性。 多聚合物熔体系统的流动诱导结晶（FIC）的微观尺度建模将研究域界面和加工条件对结晶形态发展的影响，并为细观尺度研究提供FIC材料模型。细观尺度模型将通过形状倍增元件研究熔体流的稳定性以及加工过程中相域的形成，以确定可测量的加工参数如何控制晶体形态和相域结构。材料表征和微机械建模将研究晶体和域结构对建筑共混物机械性能的影响。该项目由工程理事会土木、机械和制造创新部门和材料部门共同资助数学和物理科学理事会的研究。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。