An efficient strategy for a controllable droplet merging system for digital analysis

Abstract

Droplet merging is an important part of droplet manipulation approaches. Droplet merging methods with expansions inside channels can merge droplets in pairs through simple structures. However, they have a low success rate of merging under unstable fluidic conditions since the one-to-one pairing strategy is sensitive to fluctuation. This study presents a one-to-a-cluster pairing strategy to improve the success rate of merging under fluctuation. The one-to-a-cluster method was suitable for digital analysis and droplet MDA was performed in merged droplets successfully.