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Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization
发布时间:2024-02-23

Obtaining auxetic and isotropic metamaterials in counterintuitive design spaces: an automated optimization approach and experimental characterization 

Timon Meier, Runxuan Li, Stefanos Mavrikos, Brian Blankenship, Zacharias Vangelatos, M. Erden Yildizdag & Costas P. Grigoropoulos

npj Computational Materials 10: 3 (2023)

Editorial Summary

Theoretical Design of Metamaterials with Unique Mechanical Properties

The design of mechanical materials with tailored properties has been subject of significant interest in recent years, driven by advancements in three-dimensional manufacturing processes and optimization techniques. Lattice structures, known for their high strength-to-weight ratio, energy absorption capabilities, and structural stability, play an indispensable role in aerospace, automotive, biomedical, and energy systems. However, achieving systematic design of optimal lattice structures with multiple desired mechanical properties remains a challenging task. Conventional design methods relying on trial and error, or intuition can be time-consuming, costly, and may not guarantee optimal performance. Recent advancements in manufacturing, finite element analysis (FEA), and optimization techniques have expanded the design possibilities for metamaterials, including isotropic and auxetic structures, known for applications like energy absorption due to their unique deformation mechanism and consistent behavior under varying loads. However, achieving simultaneous control of multiple properties, such as optimal isotropic and auxetic characteristics, remains challenging. In this work, Timon Meier et al. from the Laser Thermal Laboratory, Department of Mechanical Engineering, University of California, Berkeley, addressed this challenge by employing a fully automated multi-objective design optimization approach using a genetic algorithm optimization framework. In the study, they introduced a systematic design method that combines modeling, FEA, genetic algorithms, and optimization to create lattice structures with customized mechanical properties. Through strategically arranging eight distinctly neither isotropic nor auxetic unit cell states, the stiffness tensor in a 5 × 5 × 5 cubic symmetric lattice structure was controlled. This design choice results in a large counterintuitive combinatorial design space, providing flexibility in achieving desired mechanical properties. The application of Multiphoton lithography fabrication (MPL) and experimental characterization of the optimized metamaterial highlights a practical real-world use and confirms the close correlation between theoretical and experimental data. The comprehensive methodology integrates automated design, FEA, and optimization with MPL fabrication, and experimental characterization to validate the optimal structure, offering engineers and researchers with a valuable tool for creating lattice structures with customized mechanical properties.

编辑概述

具有优异力学性能超材料的理论设计

近年来,由于三维制造工艺和优化技术的进步,定制特性的机械材料设计引起了极大的兴趣。晶格结构因其高强度-重量比、出色的能量吸收能力和卓越的结构稳定性,在航空航天、汽车、生物医学和能源系统等领域扮演着不可或缺的角色。然而,实现具有多种期望力学性能的最优晶格结构的系统设计仍然是一项具有挑战性的任务。传统的设计方法依赖于试错或直觉,可能会耗时、昂贵,而且可能不能保证最佳性能。制造、有限元分析和优化技术的最新进展扩展了超材料设计的可能性,包括各向同性和拉胀结构,因其独特的变形机制和在不同载荷下的一致行为而被用于能量吸收等应用。然而,实现多个性质的同时控制,如最佳的各向同性和辅助特性,仍然具有挑战性。在本工作中,来自加州大学伯克利分校机械工程系激光热实验室的Timon Meier等人,采用全自动多目标设计优化方法,利用遗传算法优化框架,设计出了具有定制弹性行为的晶格结构。该工作介绍了一种系统的设计方法,将模拟、有限元分析、遗传算法和优化结合起来,用于创建具有定制力学性能的晶格结构。通过战略性地排列8种明显不是各向同性也不是辅助的单位单元状态,控制了5×5×5立方对称晶格结构中的刚度张量。这种设计选择产生了一个大的违反直觉的组合设计空间,为实现所需的机械性能提供了灵活性。超材料的多光子光刻制造和实验表征突显了其现实应用,并证实了理论数据与实验数据之间的密切关联。本研究所介绍的方法集成了自动化设计、有限元分析和优化与制造,以及实验表征,以验证最优结构,本方法为工程师和研究人员提供了一个有价值的工具,用于创建具有定制的力学性能的晶格结构。

 
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