Spacing Optimization for Active Droplet Sorting in Microfluidic Networks Using Genetic Algorithm

Sorting is an important operation in droplet microfluidics. In this paper, we propose a novel, active technique for sorting of drops. The technique involves sending of drops to a one-dimensional (1D) microfluidic network at calculated time intervals. We make use of the hydrodynamic interactions to sort the drops. With the help of a simple model from the literature for the movement of drops in 1D microchannel networks, we present computational results that corroborate the use of the design of inlet spacing for active sorting of drops. Using genetic algorithm, we identified inlet spacings that are insensitive to potential experimental errors. The identified spacings can be used to completely sort a large number of drops. We also observed that for a given set of drops, identifying inlet spacing is a one-time process as this spacing would result in the same sorting efficacy for any other operating flow rate.