Inverse design of magneto-active metasurfaces and robots: Theory, computation, and experimental validation
Inverse design of magneto-active metasurfaces and robots: Theory, computation, and experimental validation
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DOI：
10.1016/j.cma.2023.116065
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发表时间：
2023-08
影响因子：
7.2
通讯作者：
Chao Wang;Zhi Zhao;X. Zhang
中科院分区：
文献类型：
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作者：
Chao Wang;Zhi Zhao;X. Zhang
磁活性结构可以在不受束缚的磁场下发生快速且可逆的变形。对于许多应用来说，设计此类结构以在磁驱动下实现三维 (3D) 可编程形状变形的能力是非常理想的。在这项工作中，我们开发了一种多物理拓扑优化框架，用于磁活性超表面的逆向设计，该超表面可以在外部磁场下进行 3D 可编程形状变形。这些超表面在其初始配置中保持平面，并变形为复杂的 3D 目标形状。所提出的框架考虑了大变形运动学，并结合外部磁场的方向和大小优化了超表面的拓扑和磁化分布。我们展示了剪纸超表面、具有“游泳”、“转向”、“行走”和“攀爬”运动的仿生机器人以及多模态磁致动器的设计框架，优化的设计在实现复杂的3D变形方面表现出高精度和高性能。我们还使用混合制造程序来制造代表性设计并进行实验测试以验证其编程的 3D 变形，结果与模拟预测吻合良好。我们设想所提出的框架可以为机器人应用的磁活性超表面设计提供一种系统且通用的方法。
Magneto-active structures can undergo rapid and reversible deformations under untethered magnetic fields. The capability to design such structures to achieve programmable shape morphing in three dimensions (3D) under magnetic actuation is highly desirable for many applications. In this work, we develop a multi-physics topology optimization framework for the inverse design of magneto-active metasurfaces that can undergo programmable shape morphing in 3D under external magnetic fields. These metasurfaces remain planar in their initial configurations and are deformed into complex 3D target shapes. The proposed framework accounts for large-deformation kinematics and optimizes both the topologies and magnetization distributions of metasurfaces in conjunction with the directions and magnitudes of the external magnetic fields. We demonstrate the framework in the design of kirigami metasurfaces, bio-inspired robots with “swimming”, “steering”, “walking”, and “climbing” motions, and multi-modal magnetic actuators, and the optimized designs show high precision and performance in achieving complex 3D deformations. We also use a hybrid fabrication procedure to manufacture representative designs and conduct experimental tests to validate their programmed 3D deformations, with results showing good agreement with simulation predictions. We envision that the proposed framework could lead to a systematic and versatile approach for the design of magneto-active metasurfaces for robotics applications.