Design automation of microfluidic droplet sorting platforms

Abstract

Both basic research and biological design require high throughput screening to parse through the massive amounts of variants generated in experiments. However, the cost and expertise needed for use of such technology limit accessibility. Simple and reproducible designs of a sorting platform would reduce the barrier for implementation of affordable bench-top screening platforms. Droplet microfluidics present a promising approach for automating biology, reducing reaction volumes to picoliter droplets and allowing for deterministic manipulation of samples. Droplet microfluidics have been used extensively for high throughput screening and directed evolution, yet limitations in fabrication have prevented the characterization needed for a design tool and subsequent widespread adoption. Here, we present a finite element analysis (FEA) model-based design framework for dielectrophoretic droplet microfluidic sorters and its preliminary experimental validation. This framework extends previous work from our group creating microfluidic designs tools, increasing their usability in the lab.