NSF-DFG: Hierarchical Design and Additive Manufacturing of Metallic Programmable Metamaterials

NSF-DFG：金属可编程超材料的分层设计和增材制造

• 批准号: 2228266
• 负责人: Xinghang Zhang
• 金额: $ 45.29万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2228266&HistoricalAwards=false
• 关键词: NSF; DFG; Hierarchical; Design; Additive

Programmable mechanical metamaterials (PMMs) have unique mechanical properties and functionalities through specific geometric designs without changing the material composition. Current PMMs are primarily made of polymer, which cannot sustain high stress and temperature. Metallic PMMs can be used under these extreme conditions, and have potential applications for aerospace, automobile and biomedical industries. However, an existing scientific challenge is that a simple translation of the proven polymer PMM design into metals is unsuccessful because most metals have magnitudes lower elastic strain limit than polymers leading to a low lifetime under cyclic loading. Without a complete structural redesign, the required mechanical properties would be extremely challenging to achieve in metallic PMMs. Although additive manufacturing (AM) offers the potential to fabricate complex geometry, the small dimension and complex geometry required to achieve functionality in metallic PMMs have reached its resolution limit. Hence, there is an urgent need to explore the fundamental AM processing mechanism that can achieve desirable small features with acceptable defect density and residual stresses. This project leverages the unique expertise of the Purdue team on manufacturing and Freiburg team on design to tackle this challenge. The international collaboration will enable students from both institutes to develop a solid foundation in both experiments and simulations through videoconferences and annual student exchanges. The objective of this project is to apply laser powder bed fusion to fabricate metallic PMMs and understand fundamentally the influence of hierarchical design and AM processing on microstructures, defect density, elastic strain limit and fatigue resistance. The project team plans to develop an integrated experimental and modeling platform that can significantly improve fundamental understandings on the manufacturing of metallic PMMs with superior mechanical performance (large global strain and fatigue resistance). This research will integrate AI-assisted computer design, AM modeling and processing, characterization and mechanical testing to identify architectures that can sustain large global strain with minimal local elastic strain. Purdue’s capability on in-situ small scale mechanical testing in SEM and Freiburg’s capability on fatigue testing of small structures will be integrated to understand the underlying deformation and fatigue mechanisms. If successful, this project will generate new knowledge about the influence of AM processing conditions on generation of internal defects and residual stress, as well as the consequent impact on fatigue properties of metallic PMMs. This project is also expected to lead to new structural redesign of PMM coupled with AM for metallic materials that offers the promise to sustain large elastic deformation, high stress and fatigue resistance, not attainable in polymeric PMMs.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.

可编程机械超材料 (PMM) 通过特定的几何设计而具有独特的机械性能和功能，而无需改变材料成分。当前的 PMM 主要由聚合物制成，无法承受高应力和温度，因此金属 PMM 可以在这些极端条件下使用。然而，现有的科学挑战是将经过验证的聚合物 PMM 设计简单地转化为金属是不成功的，因为大多数金属的弹性应变极限比聚合物低，导致使用寿命短。尽管增材制造 (AM) 具有制造复杂几何形状的潜力，但如果不进行完整的结构重新设计，实现金属粉末冶金功能所需的小尺寸和复杂几何形状将极具挑战性。 PMM 已达到其分辨率极限，因此迫切需要探索基本的增材制造加工机制，以实现具有可接受的缺陷密度和残余应力的理想小特征。该项目利用了普渡大学制造团队和弗莱堡团队的独特专业知识。设计来应对这一挑战。国际合作将使两个学院的学生通过视频会议和年度学生交流在实验和模拟方面打下坚实的基础。该项目的目标是应用激光粉末床融合来制造金属粉末冶金模型，并从根本上了解分层设计和制造的影响。微观结构、缺陷密度、弹性应变极限和抗疲劳性的增材制造处理该项目团队计划开发一个集成的实验和建模平台，可以显着提高对具有优异机械性能（大全局应变和抗疲劳性）的金属粉末冶金材料制造的基本了解。 ）。这研究将整合人工智能辅助计算机设计、增材制造建模和处理、表征和机械测试，以确定能够以最小的局部弹性应变承受大的全局应变的结构，普渡大学在扫描电镜中进行原位小规模机械测试的能力和弗莱堡大学的疲劳能力。将集成小型结构的测试，以了解潜在的变形和疲劳机制。如果成功，该项目将产生有关增材制造加工条件对内部缺陷和残余应力产生的影响以及对疲劳性能的影响的新知识。金属的该项目还预计将导致 PMM 与金属材料增材制造相结合的新结构重新设计，从而有望维持聚合物 PMM 无法实现的大弹性变形、高应力和抗疲劳性。该奖项反映了 NSF 的法定使命和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，该项目被认为值得支持。