AI 中文总结
研究针对传统粘弹性材料处理机械信号的不足，利用双稳态机械介质，通过微观布朗动力学与泊松切换耦合模拟，得出解析解，揭示信号穿透和响应现象及权衡，为智能软物质频率选择性信号处理提供设计规则。
AI 中文摘要
动态处理机械信号对软机器人技术和机械传感至关重要，而传统粘弹性材料缺乏内在可调性。研究表明内部双稳态可主动控制机械（超）材料中的响应和信号衰减。在模型中，双稳态元件在由势能ε、平衡长度Δl和弹簧常数Δk区分的状态之间以预定义时间尺度离散切换。通过微观布朗动力学与速率为ν的泊松切换耦合进行模拟，并由非线性连续场理论宏观描述。该模型得出线性响应和空间穿透深度的封闭形式解析解，揭示了普遍筛选机制和频率不敏感响应平台。筛选长度主要由构象长度变化Δl控制，衰减区域和平原可通过切换速率ν调节。系统参数研究揭示了基本设计权衡。因其解析易处理性，该框架为微调双稳态介质的自适应响应提供了明确设计规则，适用于多种实验系统。
英文摘要
Dynamically processing mechanical signals is crucial for soft robotics and mechanosensing, where classical viscoelastic materials lack intrinsic tunability. We show that internal bistability actively controls the response and signal attenuation in mechanical (meta)materials. In our model, bistable elements switch discretely with a predefined timescale between states distinguished by potential energy $ε$, equilibrium length $Δl$, and spring constant $Δk$. The system is simulated via microscopic Brownian dynamics coupled to Poisson switching with rate $ν$, and described macroscopically by a nonlinear continuum field theory. Crucially, the model yields closed-form analytical solutions for the linear response and spatial penetration depth, revealing two phenomena: a universal screening mechanism (akin to the electrostatic 'skin effect') reducing spatial signal penetration when the driving frequency exceeds the internal relaxation rate, and a frequency-insensitive response plateau from timescale separation. The screening length is controlled primarily by the conformational length change $Δl$, while the attenuation regime and plateau are tuneable via the switching rate $ν$. A systematic parameter study exposes a fundamental design trade-off: larger $Δl$ strengthens dissipation but raises the energy barrier for state transitions, eventually causing state-locking where damping vanishes. Optimal attenuation thus requires a compromise between pronounced bistability and a surmountable barrier. Due to its analytical tractability, our framework provides explicit design rules for fine-tuning the adaptive response of bistable media. It applies to diverse experimental systems-from biopolymers to synthetic catch bonds and metamaterials-enabling the predictive engineering of intelligent soft matter for frequency-selective signal processing.
