Physics of Living Systems, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA.
Science. 2021 Jan 1;371(6524):90-95. doi: 10.1126/science.abc6182.
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.
自组织在各种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难以确定。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配置相关响应。这允许导出一个类似于玻尔兹曼的原理来理解和操纵驱动的自组织。我们使用形状变化的机器人主动物质进行实验验证，并概述了一种控制集体行为的方法。我们的发现强调了如何出现的秩序取决于外部强迫模式与内部动力学响应特性之间的匹配，为设计和控制主动粒子混合物和超材料指明了未来的方法。
