Evolving programmable computational metamaterials
Evolving programmable computational metamaterials
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DOI：
10.1145/3512290.3528861
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发表时间：
2022-04
期刊：
影响因子：
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通讯作者：
Atoosa Parsa;Dong Wang;C. O’Hern;M. Shattuck;Rebecca Kramer‐Bottiglio;J. Bongard
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文献类型：
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作者：
Atoosa Parsa;Dong Wang;C. O’Hern;M. Shattuck;Rebecca Kramer‐Bottiglio;J. Bongard
数字信号处理器被广泛用于当今的计算机中以执行高级计算任务。但是，一百年前选择数字电子作为计算的物理基底，更多的是受到技术限制的影响，而不是基底的适当性。近几十年来，化学、物理和材料科学的进步提供了新的选择。颗粒状超材料是实现机械计算设备的一个有前途的目标。然而，它们的高维设计空间和微观结构与所需宏观行为之间的非直观关系使得逆设计问题变得艰巨。在本文中，我们使用多目标进化优化来解决这个逆问题：我们展示了嵌入在颗粒超材料中的基本逻辑门的设计，并且所设计的材料可以通过频率调制进行“重新编程”。随着超材料设计的进步，可以进化出计算密度更高的材料，这些材料可以通过在频域中编写的日益复杂的编程语言进行重新编程。
Digital signal processors are widely used in today's computers to perform advanced computational tasks. But, the selection of digital electronics as the physical substrate for computation a hundred years ago was influenced more by technological limitations than substrate appropriateness. In recent decades, advances in chemical, physical and material sciences have provided new options. Granular metamaterials are one such promising target for realizing mechanical computing devices. However, their high-dimensional design space and the unintuitive relationship between microstructure and desired macroscale behavior makes the inverse design problem formidable. In this paper, we use multiobjective evolutionary optimization to solve this inverse problem: we demonstrate the design of basic logic gates embedded in a granular metamaterial, and that the designed material can be "reprogrammed" via frequency modulation. As metamaterial design advances, more computationally dense materials may be evolved, amenable to reprogramming by increasingly sophisticated programming languages written in the frequency domain.