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具有独特的机械性能和功能，而无需更改材料组成。当前的PMM主要由聚合物制成，该聚合物无法维持高应力和温度。金属PMM可以在这些极端条件下使用，并在航空航天，汽车和生物医学行业中有潜在的应用。但是，现有的科学挑战是，将验证的聚合物PMM设计简单地翻译成金属是不成功的，因为大多数金属的弹性应变极限低于导致循环载荷下寿命低的聚合物。如果没有完整的结构重新设计，则需要在金属PMM中实现所需的机械性能。尽管添加剂制造（AM）提供了制造复杂几何形状的潜力，但在金属PMM中实现功能所需的小维数和复杂的几何形状已达到其分辨率限制。因此，迫切需要探索基本的AM处理机制，该机制可以实现具有可接受的缺陷密度和残留应力的理想小特征。该项目利用了Purdue团队的独特专家制造业和Freiburg团队的设计，以应对这一挑战。国际合作将使来自两家学院的学生能够通过视频会议和年度学生交流在实验和模拟中建立坚实的基础。该项目的目的是将激光粉末床融合应用于制造金属PMM，并从根本上理解层次设计和AM处理对微结构，缺陷密度，弹性应变极限和疲劳耐药性的影响。该项目团队计划开发一个集成的实验和建模平台，该平台可以显着提高对具有卓越机械性能（大全球菌株和抗疲劳性）的金属PMM制造的基本理解。这项研究将整合AI辅助的计算机设计，AM建模和处理，表征和机械测试，以识别可以使用最小的局部弹性应变维持大全球应变的体系结构。普渡大学在SEM中的原位小规模机械测试和弗莱堡对小结构的疲劳测试的能力，如果成功，该项目将产生有关AM加工条件对内部缺陷和残留应力产生的影响的新知识，以及随之而来的对金属PMMS疲劳特性的影响。预计该项目还会导致PMM的新结构重新设计，加上AM的金属材料，提供了具有巨大的弹性变形，高压力和抗疲劳性的承诺，在聚合PMM中无法获得，这反映了NSF的法规任务，并通过评估诚实地使用基金会的知识分子来评估NSF的法规任务，并诚实地通过评估来进行评估。