DMREF/Collaborative Research: Iterative Design and Fabrication of Hyperuniform-Inspired Materials for Targeted Mechanical and Transport Properties

微晶格和纳米晶格结构是一类令人兴奋的材料，具有比大块固体更好的强度/重量比和刚度/重量比。最近出现了许多设计和添加剂制造方法(即3D打印)来创造这种材料，目标是制造具有优化的机械、热、声和电性能的商业可用产品，用于生物医学、航空航天和其他几个应用。设计材料革新和设计我们的未来(DMREF)基金将支持开发新的方法来设计一类新的无序晶格材料，这些材料的灵感来自于所谓的“超均匀”结构的特殊传输特性，例如热传递和扩散。超均匀材料名义上可以被描述为密度随长度尺度的增加而变化最小的材料。它们自然地出现在生物和化学系统中，并可以通过数值方法进行设计。大量研究表明，这种系统以最小的衰减促进了有效的传输行为，同时还具有近乎最佳的有效弹性刚度和材料断裂抑制。这笔拨款还将为工程、材料科学、数学和物理等多学科领域的本科生、博士后和博士后研究人员提供有效的劳动力发展。它将通过出版物、外展和针对高中生和教师的实习计划来帮助公众理解材料研究。此外，还将努力发展企业家精神，并支持学员将其想法商业化。该项目的目标是设计一种新的超轻可制造材料，具有共同优化的机械(硬度和强度)和运输(热、声和电)性能。为了实现这一目标，该方法包括：(1)表征和了解利用局部一致性和超一致性的好处；(2)测量机械和传输性能，以创建和了解这些材料的结构-工艺-性能图，包括异质性和缺陷的影响；以及(3)开发新的计算工具，允许在材料开发的整个理论、合成和实验循环中进行优化。研究活动将遵循三条属性共同优化的路线：(1)调整初始配置，包括连通性(理论)；(2)材料选择和控制由添加剂制造过程产生的微观异质性(合成)；(3)设计时变信号，在应用于结构时产生特定的空间相关性(实验)。该方法还将包括新的建模方法，如创建设计启发式的网络分析和考虑微观异质性的高阶随机空间平均技术。这些模型将通过允许创建随机网络模型来高效地反馈到设计过程中，这些模型生成的特定功能也仍然可以制造。构成研究目标基础的设计周期在很大程度上依赖于构建共享的配置库和代码库；这些将被发布以供其他研究小组使用。该项目由工程局(ENG)的土木、机械和制造业创新处(CMMI)和数学科学局(DMS)的数学科学部(DMS)和数学和物理科学局(MPS)的材料研究部(DMR)支持。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，认为值得支持。

Micro-lattice and nano-lattice structures are an exciting class of materials with better strength-to-weight and stiffness-to-weight ratios than bulk solids. Many designs and additive-manufacturing approaches (i.e., 3D printing) have emerged recently for creating such materials, with the goal of fabricating commercially available products with optimized mechanical, thermal, acoustic, and electrical properties for biomedical, aerospace, and several other applications. This Designing Materials to Revolutionize and Engineer our Future (DMREF) grant will support development of novel approaches to design a new class of disordered lattice materials that are inspired by the special transport properties, e.g., heat transfer and diffusion, of the so-called “hyperuniform” structures. Hyperuniform materials may nominally be described as materials with minimal density variation as the length scale increases. They arise naturally in biological and chemical systems and can be designed through numerical methods. Numerous studies have demonstrated that such systems facilitate efficient transport behavior with minimal attenuation while also possessing nearly optimal effective elastic stiffness and material fracture suppression. The grant will also provide effective workforce development for a diverse group of undergraduates, PhD students, and postdoctoral researchers in the multidisciplinary areas of engineering, materials science, mathematics, and physics. It will contribute to the public understanding of materials research via publications, outreach, and internship programs for high-school students and teachers. Additionally, there will be an effort to develop entrepreneurship and trainees will be supported in pursuing commercialization of their ideas. The objective of this project is to engineer a new class of ultralight, manufacturable materials with jointly optimized mechanical (stiffness and strength) and transport (thermal, acoustic, and electrical) properties. To achieve this, the approach includes (1) characterization and understanding of the benefits of exploiting local uniformity and hyperuniformity; (2) measurement of mechanical and transport properties to create and understand the structure–process–property diagram for these materials, including the influence of heterogeneity and defects; and (3) development of new computational tools that allow optimization throughout the integrated theory, synthesis, and experiment loop of material development. The research activities will pursue three routes for property co-optimization: (1) adjustments to the initial configuration, including connectivity (theory); (2) material selection and control of microscale heterogeneity that is created by the additive-manufacturing process (synthesis); (3) designing time-varying signals that create specified spatial correlations when applied to structures (experiment). The approach will also include new modeling approaches, such as network analysis to create design heuristics and higher-order stochastic spatial-averaging techniques to account for microscale heterogeneity. These models will efficiently feed back into the design process by allowing the creation of random-network models that generate specific features that also remain manufacturable. The design cycle that forms the basis of the research aims draws heavily on building a shared Configuration Library and Code Library; these will be published for use by other research groups. This project is supported by the Division of Civil, Mechanical and Manufacturing Innovation (CMMI) of the Directorate for Engineering (ENG) and the Division of Mathematical Sciences (DMS) and the Division of Materials Research (DMR) of the Directorate for Mathematical and Physical Sciences (MPS).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.