FMSG: Cyber: Does Nature Invoke the Optimum? A Bioinspired Hierarchical Manufacturing Process

这项未来制造业补助金旨在通过仿生和生物启发方法支持创新设计制造的进步，为国家的繁荣和进步奠定基础。自然生物是适应性设计的突出范例。通过数百万年的进化经验，它们在适应环境中制造自己，以应对外部刺激。自然界设计的多功能性和复杂性需要层次特征，从微米到纳米的长度尺度。这些有趣的设计包括复杂的结构特征和增强的机械性能。我们能从自然设计中学到什么？更重要的是，我们能否在他们成功的基础上做得更好？从力学行为的角度来看，使用特定的设计参数来系统地定义设计空间几乎是不成功的。因此，即使这些设计是有效的，也不能保证它们也是最优的。该奖项支持基础研究，以揭示设计最佳仿生/仿生结构所需的建模、优化和制造过程。该项目的成功完成将为这些结构在组织工程、先进材料和增强结构中的应用铺平道路，成为美国经济和社会的催化剂。学生和博士后将参与并接受培训。增材制造的最新进展使复杂多功能结构的制造成为可能。这一进展已经在社会的各个方面引入了仿生和生物启发设计的应用，从结构工程到生物工程。虽然存在建模和实验工具来分析自然的最终创造，但它们仍然没有合并在一个战略和连贯的方案中，以解开设计过程的中间步骤，并阐明如何在建筑材料的制造和设计过程中利用每个步骤。本研究的目标是设计和制造具有复杂的多尺度分层结构的三维（3D）生物灵感结构，包括它们的组成，尺寸和几何形状。为了预测在特定时间框架内基于外部刺激的结构发展，将开发三维生长连续体力学建模技术。此外，多尺度印刷技术将被开发，以制造宏观尺度和微/纳米尺度的特征，模仿自然界通过生长的分层“制造”过程。通过随机优化技术与先进的机器学习算法增强，设计空间和最优的识别将被探索。最后，以自然界为参照，通过先进的表征技术，包括原位扫描电镜测试，将算法找到的最优结果与实际的自然生物进行比较。这项研究的发现将表明，来自大自然的教训不仅是如何被模仿的，而且还可以导致新的方法，从而为这个问题提供答案：大自然是否激发了最佳状态？基于这项工作，将有可能展示一种能够生产高机械性能结构的制造策略，表现出弹性和损伤容忍度。该项目由数学和物理科学理事会（MPS）的数学科学部（DMS）和工程理事会（ENG）的工业创新和伙伴关系（IIP）共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This Future of Manufacturing grant aims to support advances in the manufacturing of innovative designs through biomimetic and bioinspired methodologies, setting the framework for the national prosperity and progress. Natural organisms are prominent paradigms of adaptive design. Through millions of years of evolutionary experiences, they fabricate themselves in an adaptive environment, in response to external stimuli. The versatility and complexity of nature’s design arsenal entails hierarchical features, at length scales of micrometers to nanometers. These intriguing designs involve perplexing structural features and enhanced mechanical performance. What can we learn from natural designs? Even more, can we do better by building on their success? From the perspective of the mechanical behavior, there is little success in a systematic definition of the design space using specific design parameters. Hence, even though these designs are effective, there is no guarantee that they are also optimal. This award supports the fundamental research required to unveil the modeling, optimization and fabrication processes necessary to design optimal biomimetic/bioinspired structures. The successful completion of this project will pave the way for the utility of these structures in tissue engineering, advanced materials, and augmented structures, becoming a catalyst for the U.S. economy and society. Students and postdocs will be involved and trained. Recent advances in additive manufacturing have enabled the fabrication of complex multifunctional structures. This progress has introduced the utility of biomimetic and bioinspired designs in every aspect of society, spanning from structural engineering to bioengineering. While modeling and experimental tools exist to analyze the final creation of nature, they have still not been merged in a strategic and coherent scheme to unravel the intermediate steps of the design process and elucidate how each step can be exploited in the manufacturing and design process of architected materials. The goal of this research is to design and fabricate three dimensional (3D) bioinspired structures with sophisticated multiscale hierarchical structure regarding their composition, dimensions, and geometry. To predict the structural development based on the external stimuli within a specific time frame, 3D growth continuum mechanics modeling techniques will be developed. In addition, multiscale printing techniques will be developed to fabricate both macroscale and micro/nanoscale features imitating the hierarchical “fabrication” process of nature through growth. Through stochastic optimization techniques augmented with advanced machine learning algorithms, the design space and identification of optima will be explored. Finally, using nature as reference, the optimum found by the algorithm will be compared with the actual natural organism through advanced characterization techniques, including in situ scanning electron microscopy tests. The findings of this research will show how lessons from nature are not merely imitated, but they can lead to novel approaches that will provide an answer to the question: Does Nature Invoke the Optimum? Based on this work, it will be possible to demonstrate a manufacturing strategy capable of producing structures of high mechanical performance, exhibiting resilience and damage tolerance.This project is jointly funded by the Division of Mathematical Sciences (DMS) within the Directorate of Mathematical and Physical Sciences (MPS), and by Industrial Innovation and Partnerships (IIP) within the Directorate of Engineering (ENG).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.