AI 中文总结
该研究基于粒子模拟与Quincke滚轮混合物实验，利用速度差异和曲率构建微流控装置，实现二元混合物的高效连续分选，为自主微流控分离提供新途径。
AI 中文摘要
我们利用集体相分离的两个成熟要素：速度差异和曲率，构建自分选装置。在二元混合物中，运动性差异驱动自发空间分离，而受限几何结构决定该相分离发生的速度与强度。通过基于粒子的模拟，我们系统确定促进高效分离的几何条件，并利用这些结果指导有限分选架构的设计。随后，我们将这些物理机制转化为一系列弯曲的微流控单元，逐步放大两种物质的分离效果，并将其引导至不同收集区域。对二元Quincke滚轮混合物的实验证实，初始混合悬浮液在通过装置时会逐步发生相分离，最终在下游实现强烈富集。我们的结果表明，集体主动相分离可转化为功能性连续分选策略，为基于粒子运动性和受限几何结构的自主微流控分离提供了途径。
英文摘要
We harness two established ingredients for collective demixing: differential speed and curvature to create a self-sorting device. In binary mixtures, motility differences drive spontaneous spatial segregation, while confinement geometry determines how rapidly and strongly this demixing develops. Using particle based simulations, we systematically identify the geometrical conditions that promote efficient segregation and use these results to guide the design of a finite sorting architecture. We then translate these physical mechanisms into a sequence of curved microfluidic units that progressively amplify the separation of the two species and direct them toward distinct collection regions. Experiments with binary Quincke-roller mixtures confirm that an initially mixed suspension progressively demixes as it propagates through the device, leading to strong enrichment downstream. Our results demonstrate how collective active demixing can be converted into a functional continuous sorting strategy, providing a route toward autonomous microfluidic separation based on particle motility and confinement geometry.
