De Novo Atomistic Discovery of Disordered Mechanical Metamaterials by Machine Learning
De Novo Atomistic Discovery of Disordered Mechanical Metamaterials by Machine Learning
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DOI：
10.1002/advs.202304834
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发表时间：
2024-01-25
期刊：
影响因子：
15.1
通讯作者：
Bauchy，Mathieu
中科院分区：
文献类型：
--
作者：
Liu，Han;Li，Liantang;Bauchy，Mathieu
建筑材料的设计跨越数量级的长度尺度，体现了在其自然体状态下不存在的特殊机械响应。然而，所谓的机械超材料，当按比例缩小到原子或微粒水平时，仍然在很大程度上未被探索，并且通常会超出其粗分辨率，有序图案设计空间。在这里，结合高通量分子动力学（MD）模拟和机器学习（ML）策略，发现了一些有趣的无序机械超材料的原子家族，如通过熔融淬火制造的，并在本文中以具有线性刚度密度缩放的理论极限的轻质但刚性的蜂窝材料为例，其结构无序-而不是有序-是降低标度指数的关键，并且简单地由键合相互作用及其方向性控制，这使得实验上能够实现灵活的可调谐性。重要的是，力场景观中的系统导航显示，在方向性和非方向性键合（如共价键和离子键）之间，适度的键方向性最有可能促进多面体的无序堆积，拉伸主导的结构负责形成超材料。这项工作开创了一种自下而下的原子方案，以设计无序格式化的机械超材料，解锁了一个在原子上利用结构无序设计超材料的基本上未开发的领域，并且可能通用于传统的升级设计。
Architected materials design across orders of magnitude length scale intrigues exceptional mechanical responses nonexistent in their natural bulk state. However, the so‐termed mechanical metamaterials, when scaling bottom down to the atomistic or microparticle level, remain largely unexplored and conventionally fall out of their coarse‐resolution, ordered‐pattern design space. Here, combining high‐throughput molecular dynamics (MD) simulations and machine learning (ML) strategies, some intriguing atomistic families of disordered mechanical metamaterials are discovered, as fabricated by melt quenching and exemplified herein by lightweight‐yet‐stiff cellular materials featuring a theoretical limit of linear stiffness–density scaling, whose structural disorder—rather than order—is key to reduce the scaling exponent and is simply controlled by the bonding interactions and their directionality that enable flexible tunability experimentally. Importantly, a systematic navigation in the forcefield landscape reveals that, in‐between directional and non‐directional bonding such as covalent and ionic bonds, modest bond directionality is most likely to promotes disordered packing of polyhedral, stretching‐dominated structures responsible for the formation of metamaterials. This work pioneers a bottom‐down atomistic scheme to design mechanical metamaterials formatted disorderly, unlocking a largely untapped field in leveraging structural disorder in devising metamaterials atomistically and, potentially, generic to conventional upscaled designs.