Low rattling: A predictive principle for self-organization in active collectives
Low rattling: A predictive principle for self-organization in active collectives
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DOI：
10.1126/science.abc6182
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发表时间：
2021-01-01
期刊：
影响因子：
56.9
通讯作者：
England, Jeremy L.
中科院分区：
文献类型：
--
作者：
Chvykov, Pavel;Berrueta, Thomas A.;England, Jeremy L.
自组织在活跃的集体中经常被观察到，如蚂蚁筏和分子马达组件。描述远离平衡的自组织的一般原则一直很难确定。我们提供了一个统一的框架，该框架将复杂系统的行为建模为很大程度上是随机的，同时捕获它们对外部强迫的依赖于配置的响应。这允许推导出一个类似玻尔兹曼的原理，用于理解和操纵驱动自组织。我们通过实验验证了我们的预测，使用形状变化的机器人活性物质，并概述了控制集体行为的方法。我们的研究结果强调了紧急秩序如何敏感地依赖于外部强迫模式和内部动态响应特性之间的匹配，指出了未来设计和控制活性粒子混合物和超材料的方法。
Self-organization is frequently observed in active collectives as varied as ant rafts and molecular motor assemblies. General principles describing self-organization away from equilibrium have been challenging to identify. We offer a unifying framework that models the behavior of complex systems as largely random while capturing their configuration-dependent response to external forcing. This allows derivation of a Boltzmann-like principle for understanding and manipulating driven self-organization. We validate our predictions experimentally, with the use of shape-changing robotic active matter, and outline a methodology for controlling collective behavior. Our findings highlight how emergent order depends sensitively on the matching between external patterns of forcing and internal dynamical response properties, pointing toward future approaches for the design and control of active particle mixtures and metamaterials.