可重编程非线性动力学超材料的自动化发现
Automated discovery of reprogrammable nonlinear dynamic metamaterials
AI总结：
该研究提出基于全可微仿真的逆向设计框架，自动发现并实验验证可实现能量聚焦、动态防护等任务且能通过预压缩重编程的柔性机械超材料。
摘要：
利用高可变形材料丰富的非线性动力学，有望解锁下一代功能性智能材料与器件。然而，要释放这种潜力，需要有效的策略来在空间上设计最优材料架构，以实现所需的非线性动态响应，例如非线性弹性波导引、能量聚焦和隐身。在此，我们提出一种逆向设计框架，用于发现具有目标非线性动态响应的柔性机械超材料。所需动态任务通过对全尺度超材料几何结构进行最优调谐来编码，而这一逆向设计方法由自主开发的全可微仿真环境驱动。通过部署该策略，我们设计了分别面向能量聚焦、能量分束、动态防护和非线性运动转换的机械超材料。此外，我们阐明该设计框架可扩展用于自动发现能够在不同动态任务之间切换的可重编程架构。例如，我们将能量聚焦与动态防护这两个强烈竞争的任务编码到单一架构中，并利用静态预压缩在这些行为之间切换。所发现的设计得到了物理实现和实验测试，证明了工程化任务的鲁棒性。总体而言，我们的方法为获得具有定制化、类机器人可重编程功能的设计师材料开辟了一条尚未开发的途径。
英文摘要：
Harnessing the rich nonlinear dynamics of highly-deformable materials has the potential to unlock the next generation of functional smart materials and devices. However, unlocking such potential requires effective strategies to spatially design optimal material architectures for desired nonlinear dynamic responses such as guiding of nonlinear elastic waves, energy focusing, and cloaking. Here, we introduce an inverse-design framework for the discovery of flexible mechanical metamaterials with a target nonlinear dynamic response. The desired dynamic task is encoded via optimal tuning of the full-scale metamaterial geometry through an inverse-design approach powered by a custom-developed fully-differentiable simulation environment. By deploying such strategy, we design mechanical metamaterials tailored for energy focusing, energy splitting, dynamic protection, and nonlinear motion conversion. Furthermore, we illustrate that our design framework can be expanded to automatically discover reprogrammable architectures capable of switching between different dynamic tasks. For instance, we encode two strongly competing tasks -- energy focusing and dynamic protection -- within a single architecture, utilizing static pre-compression to switch between these behaviors. The discovered designs are physically realized and experimentally tested, demonstrating the robustness of the engineered tasks. All together, our approach opens an untapped avenue towards designer materials with tailored robotic-like reprogrammable functionalities.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
