Veenstra Jonas, Scheibner Colin, Brandenbourger Martin, Binysh Jack, Souslov Anton, Vitelli Vincenzo, Coulais Corentin
Institute of Physics, Universiteit van Amsterdam, Amsterdam, The Netherlands.
James Franck Institute, University of Chicago, Chicago, IL, USA.
Nature. 2025 Mar;639(8056):935-941. doi: 10.1038/s41586-025-08646-3. Epub 2025 Mar 12.
Active systems composed of energy-generating microscopic constituents are a promising platform to create autonomous functional materials that can, for example, locomote through complex and unpredictable environments. Yet coaxing these energy sources into useful mechanical work has proved challenging. Here we engineer active solids based on centimetre-scale building blocks that perform adaptive locomotion. These prototypes exhibit a non-variational form of elasticity characterized by odd moduli, whose magnitude we predict from microscopics using coarse-grained theories and which we validate experimentally. When interacting with an external environment, these active solids spontaneously undergo limit cycles of shape changes, which naturally lead to locomotion such as rolling and crawling. The robustness of the locomotion is rooted in an emergent feedback loop between the active solid and the environment, which is mediated by elastic deformations and stresses. As a result, our active solids are able to accelerate, adjust their gaits and locomote through a variety of terrains with a similar performance to more complex control strategies implemented by neural networks. Our work establishes active solids as a bridge between materials and robots and suggests decentralized strategies to control the nonlinear dynamics of biological systems, soft materials and driven nanomechanical devices.
由能产生能量的微观成分组成的活性系统是创造自主功能材料的一个有前景的平台,例如,这种材料能够在复杂且不可预测的环境中移动。然而,要将这些能源转化为有用的机械功已被证明具有挑战性。在此,我们基于厘米级构建块设计了能进行自适应移动的活性固体。这些原型展现出一种以奇模量为特征的非变分弹性形式,我们使用粗粒化理论从微观层面预测了其模量大小,并通过实验进行了验证。当与外部环境相互作用时,这些活性固体自发地经历形状变化的极限环,这自然会导致滚动和爬行等移动。移动的稳健性源于活性固体与环境之间由弹性变形和应力介导的一种涌现反馈回路。因此,我们的活性固体能够加速、调整步态,并在各种地形上移动,其性能与神经网络实施的更复杂控制策略相似。我们的工作将活性固体确立为材料与机器人之间的桥梁,并提出了控制生物系统、软材料和驱动纳米机械设备非线性动力学的分散策略。