Experimental Validation and Efficiency Analysis of Density-Based Particle-Sorting Microfluidic Devices
Please login to view abstract download link
In this work, we use a finite element-based numerical method to analyze the efficiency of density-based particle-sorting microfluidic devices. These devices exploit small density variations among different particle types to classify them by maintaining a stratified flow of fluid layers with different densities, allowing particles to drift to their equilibrium positions as they move along the circuit. Previous work did not take into account the diffusion phenomena of the density layers, which can blur the fluid interfaces and spoil the stratification. We investigate how diffusion affects the migration of the cells along the tube, and its implications for device performance. Our analysis is supported by experimental validation using real microfluidic devices. Additionally, we explore how a stabilized finite element method can be leveraged to develop a more efficient computational approach for optimizing these systems.