流体滞后元件与流动网络中的记忆
Fluidic hysterons and memory in flow networks
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中文总结 AI 辅助
研究通过流体动力学途径实现滞后元件物理，一根弹性纤维在微流体通道中经非线性反馈变双稳态，平行旁路通道可调节。在阵列中改变几何参数能驱动状态转变，建立了由流动结构反馈和水力约束产生记忆的滞后元件网络被动途径。
中文摘要 AI 辅助
滞后元件为驱动物质中的记忆提供了一种最小化描述：具有不同开关阈值的双稳态元件，其相互作用会产生滞后、雪崩以及返回点记忆或其违背现象。迄今为止，实验实现主要由固态机械系统主导，其中双稳态通常通过屈曲、快速通过或几何不相容性在结构上进行编码。在此，我们通过流体动力学途径实现滞后元件物理。一根固定在微流体通道中的弹性纤维通过非线性弹性流体动力学反馈变为双稳态：粘性负载使纤维变形，变形重塑水力阻力，流动再分布改变负载。这种反馈产生一个流体滞后元件，其起始由几何控制参数中的尖点突变组织。一个平行旁路通道充当几何负载线，可重塑甚至消除双稳态，同时介导纤维之间的长程水力相互作用。在阵列中，改变单个几何参数会驱动从具有返回点记忆的非相互作用Preisach regime到具有雪崩状开关和返回点记忆违背的相互作用状态的转变。这些结果建立了一条通往滞后元件网络的被动流体动力学途径，其中记忆源于流动结构反馈和全局水力约束，而非固态多稳定性或外部控制。
英文摘要
Hysterons provide a minimal description of memory in driven matter: bistable elements with distinct switching thresholds whose interactions generate hysteresis, avalanches, and return point memory or its violation. Experimental realizations have so far been dominated by solid state mechanical systems, where bistability is usually encoded structurally through buckling, snap through, or geometric incompatibility. Here we realize hysteron physics through a hydrodynamic route. A single elastic fiber anchored in a microfluidic channel becomes bistable through nonlinear elastohydrodynamic feedback: viscous loading deforms the fiber, deformation reshapes hydraulic resistance, and flow redistribution modifies the loading. This feedback produces a fluidic hysteron whose onset is organized by a cusp catastrophe in geometric control parameters. A parallel bypass channel acts as a geometric load line that reshapes, and can even eliminate, bistability while simultaneously mediating long ranged hydraulic interactions between fibers. In arrays, varying a single geometric parameter drives a transition from a non interacting Preisach regime with return point memory to an interacting regime with avalanche like switching and return point memory violation. These results establish a passive hydrodynamic route to hysteron networks, in which memory emerges from flow structure feedback and global hydraulic constraints rather than solid state multistability or external control.
