Collective rheotaxis of particles in a channel flow

We use computational modeling to investigate the collective rheotaxis of chemically-fueled, autonomously motile particles confined in a microfluidic channel. Rheotaxising particles rotate to move against an imposed flow. Each particle in our model is partially coated with catalysts, which convert the reagent in solution and thereby produce a local chemical gradient. The particle moves autonomously in response to this self-generated gradient. The interplay among the hydrodynamic interactions due to autonomous motion, externally imposed flow in a channel and motion in response to the chemical gradient generated by neighboring particles leads to a rich and complex behavior. To study this behavior, we use an approach that combines the immersed boundary and lattice Boltzmann techniques. The reagents are modeled as scalar fields that undergo diffusion, are advected with the background fluid flow, and are converted to product in the presence of the catalyst. We isolate the parameter space favorable for rheotaxis and quantify the collective behavior of the particles. Our findings are crucial to controlling the complex collective movement of autonomously motile particles in microfluidic devices.