标题： 纠缠颗粒网络中的渗流转变 显示英文标题

标题： Percolation transition in entangled granular networks

摘要： 高度非凸的颗粒，如图钉和金属碎屑，可以通过几何缠绕（互锁）形成类似固体的粘结结构。这种缠绕形成的网络结构，然而，仍大多未被探索。在这里，我们利用网络科学通过实验和模拟研究C形颗粒在振动下的缠绕网络。通过分析关键网络属性，我们证明了这些网络随着链接数随时间对数增加而经历渗透转变；当链接数超过临界阈值时，缠绕颗粒形成一个巨大簇。我们提出了一种环的连续渗透模型，能够有效描述观察到的转变。此外，我们发现颗粒的开口角度显著影响机械结合，从而影响网络结构。这项工作突显了基于网络的方法研究缠绕材料的潜力，为从机械超材料到缠绕机器人集群的应用进步铺平了道路。 显示英文摘要

摘要： Highly nonconvex granular particles, such as staples and metal shavings, can form solid-like cohesive structures through geometric entanglement (interlocking). The network structure formed by this entanglement, however, remains largely unexplored. Here we utilize network science to investigate the entanglement networks of C-shaped granular particles under vibration through experiments and simulations. By analyzing key network properties, we demonstrate that these networks undergo a percolation transition as the number of links increases logarithmically over time; the entangled particles form a giant cluster when the number of links exceeds a critical threshold. We propose a continuum percolation model of rings that effectively describes the observed transition. Additionally, we find that particle's opening angle significantly affects mechanical bonding and, consequently, the network structure. This work highlights the potential of network-based approaches to study entangled materials, paving the way for advancements in applications ranging from mechanical metamaterials to entangled robot swarms.