The dynamic behaviors, specifically trapping and sorting, of active particles interacting with periodic substrates have garnered significant attention. This study investigates numerically the trapping of soft, deformable particles on a periodic potential substrate, which can be experimentally verified through optical tweezers. The research demonstrates that multiple factors, including the relative size of traps, self-propelled velocity, shape parameters, ratio of particles to traps, and translational diffusion, can influence the trapping effect. Within certain parameter boundaries, it is shown that all particles can be consistently trapped. The research reveals that stable trapping typically occurs at median values of the relative trap size. An increase in the self-propelled velocity, the shape parameter, and the translational diffusion coefficient tends to facilitate the escapement of the particles from the traps. It is noteworthy that particles with larger shape parameters can escape even when the restoring force exceeds the self-propelled force. In addition, as the ratio of particles to traps grows, the fraction of trapped particles steadily reduces. Notably, rigid particles are consistently divided and trapped by traps closely approximating an integer multiple of the particles' area, up until the ratio reaches the aforesaid integer value. These findings can potentially enhance the understanding of the interactive effects between active deformable particles and periodic substrates. Moreover, this work suggests a different experimental approach to sort active particles based on rigidity disparities.

中文翻译：

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通过周期性背景电势捕获可变形活性粒子

活性粒子与周期性基底相互作用的动态行为，特别是捕获和分选，引起了人们的广泛关注。这项研究以数值方式研究了周期性势基底上柔软、可变形粒子的捕获，这可以通过光镊进行实验验证。研究表明，多种因素，包括陷阱的相对尺寸、自驱动速度、形状参数、颗粒与陷阱的比例以及平移扩散，都会影响捕获效果。在某些参数边界内，所有粒子都可以被一致地捕获。研究表明，稳定的捕获通常发生在相对捕获尺寸的中值处。自推进速度、形状参数和平移扩散系数的增加往往有利于颗粒从陷阱中逸出。值得注意的是，即使恢复力超过自推进力，形状参数较大的颗粒也可以逃逸。此外，随着粒子与陷阱的比例增加，捕获粒子的比例稳步减少。值得注意的是，刚性颗粒始终被接近颗粒面积整数倍的陷阱分开和捕获，直到比率达到上述整数值。这些发现可能会增强对主动可变形粒子和周期性基底之间相互作用效应的理解。此外，这项工作提出了一种不同的实验方法来根据刚性差异对活性颗粒进行分类。