An optimized MOPSA algorithm for highly accurate deterministic lateral displacement microfluidic sorting chip design

Abstract Deterministic lateral displacement (DLD) sorting is a passive sorting technology. Due to the advantages of small volume and high accuracy, the DLD devices have been used in many applications. The critical diameter (Dc) value of the DLD device depends on the geometric structure of the internal post array. However, the existing empirical formula cannot match all types of post-arrays. Achieving the desired Dc value typically involves multiple iterative processes, leading to increased labor and time costs. In this paper, we propose an optimized trajectory prediction algorithm based on the original MOPSA, which considers the impact of fluidic pressure on particle trajectories. The method is to stretch the 2D physical field space into 3D, the particle expands from a 2D circle into a 3D ball on the pressure analysis. The net pressure on the particle is calculated, and the displacement of the particle is predicted by combining Newton’s second law and the displacement formula. A DLD device with Dc=10.6 μm was designed using this optimized algorithm and fabricated. It is verified by separation of 10 μm and 11 μm polystyrene particles. The test results were consistent with the simulation results. Compared with the empirical formula and the original MOPSA, this optimized algorithm can improve the prediction accuracy of particle trajectories in DLD devices.