Active particles can take energy from their environment and drive themselves far from equilibrium. They feature a series of novel collective behaviors. In most active ratchet systems, active particles are considered to be moving in the overdamped regime (at the low Reynolds number regime). However, the overdamped approximation is not justified in many situations. In the systems of high Reynolds number regime, damping is significantly reduced so that inertial effects can play an important role. The coupling of inertia to self-propulsion may play a pivotal role in generating new self-organization effects. Therefore, non-equilibrium dynamics in the overdamped regime cannot well describe inertial active particles. This project will study inertial effects on the non-equilibrium dynamics (spontaneous rectified transport, diffusion, and collective behavior) of self-propelled particles by using non-equlibrium statistical methods and Langevin simulations. From this project, on the one hand, the theory of non-equilibrium statistical dynamics can be extended from overdamped particles to underdamped particles, from non-chiral particles to chiral active particles, from non-interacting particles to interacting particles, on the other hand, our studies can be applied to the experimental studies of active soft matter and biological cells for giving theoretical explanation and guidance.
活性粒子具有自驱动能力和非平衡特性,能表现出自发整流输运和一些新奇的集体现象。目前,大多数的活性棘齿系统中,活性粒子被认为是在过阻尼机制下(低雷诺数)。然而,过阻尼近似在很多情况下是不合理的,在高雷诺数机制系统下,阻尼大幅度降低以至于粒子的惯性效应起了重要作用。惯性与自驱动的耦合将在产生的新自组织效应中发挥关键作用,过阻尼下粒子的非平衡统计规律不再适用。为解决该问题,本项目以惯性活性粒子为研究对象,采用朗之万方程及非平衡统计理论研究体系,系统研究惯性活性粒子非平衡统计特性(整流,扩散和集体行为)。通过项目开展,一方面把小体系随机动力学理论从过阻尼机制推广到欠阻尼机制,从非手征粒子推广到手征活性粒子,从非相互作用粒子推广到相互作用粒子,丰富非平衡统计物理框架;另一方面,相关研究可为物理,生物和化学领域中活性物质和生物细胞的实验提供理论解释和指导。
在高雷诺数机制系统下,阻尼大幅度降低以至于粒子的惯性效应起了重要作用。惯性与自驱动的耦合将在产生的新自组织效应中发挥关键作用,过阻尼下粒子的非平衡统计规律不再适用。为解决该问题,本项目以惯性活性粒子为研究对象,采用朗之万方程及非平衡统计理论研究体系,系统研究惯性活性粒子非平衡统计特性(整流,扩散和集体行为)。本项目的研究结果,把小体系随机动力学理论从过阻尼机制推广到了欠阻尼机制,从非手征粒子推广到了手征活性粒子,从微观动力学的研究推广到了宏观非平衡结构,从短程排斥作用推广到了对齐相互作用,丰富了非平衡统计物理框架。项目资助下,共发表SCI论文6篇,北大中文核心论文1篇,专著1本。
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数据更新时间:2023-05-31
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