发表机构
University of Illinois Urbana-Champaign; National Center for Supercomputing Applications（伊利诺伊大学厄巴纳-香槟分校; 国家超级计算应用中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究模块化软超材料中局部变形传输问题，提出阻抗引导设计框架，通过建立非线性模型和拓扑优化实现可编程传输，合成模块族，实现多种位移操纵架构及信息处理，为智能材料系统提供见解和途径。
AI 中文摘要
软超材料为机器人技术、生物医学设备和柔性电子学提供了一个很有前景的平台。非均匀激励引起的局部力学响应在软材料中普遍存在，但在超材料设计中，其在组件间的可控传输在很大程度上被忽视，这严重限制了端到端和远程变形传输的重要功能。本文介绍了一种阻抗引导设计框架，通过建立考虑位置相关相互作用的非线性模型并整合超材料中的机械阻抗概念，仅通过单胞拓扑优化来调节组件级传输，实现了模块化软超材料中局部变形的可编程传输。利用该框架合成了模块族，实现了多种按需位移操纵架构，还能嵌入电逻辑信号用于信息处理。该方法为模块化软超材料中局部变形传输提供了基本见解，为实现智能材料系统建立了可扩展途径。
英文摘要
Soft metamaterials provide a promising platform for robotics, biomedical devices, and flexible electronics. The localized mechanical responses by nonuniform excitation are ubiquitous in soft materials, yet their controlled transmission across assemblies remains largely overlooked in metamaterial design, which critically constrains nontrivial functionalities with end-to-end and long-range deformation transmission. Here, we introduce an impedance-guided design framework that enables programmable transmission of localized deformation in modular soft metamaterials, achieving behaviors unattainable by intuitive design. By establishing a nonlinear model considering position-dependent interactions and integrating the concept of mechanical impedance within metamaterials, we regulate assembly-level transmission solely through unit-cell topology optimization. The resulting framework enables effective synthesis of module families, allowing both homogeneous and heterogeneous assemblies to be custom-built with markedly enhanced transmission characteristics. Leveraging the highly combinatorial and extensible design space, we physically realize diverse on-demand displacement manipulation architectures, including obstacle-bypassing modular soft-metamaterial assemblies, defect-tolerant soft gripping, and embodied signal processing. Beyond deformation programming, the reconfigurability and reassemblability of these soft modules can embed electric logic signals, enabling energy-efficient and low-latency information processing through compliant-switch-controlled mechanical LED displays and wearable finger-motion-sensing controllers. Our method provides fundamental insights into localized deformation transmission in modular soft metamaterials and establishes a scalable route toward embodied-intelligence material systems, particularly for soft-metamaterial-centric actuation, sensing, and collective computing.
