Robust sample preparation on digital microfluidic biochips

Abstract

Sample preparation is an important application for the digital microfluidic biochips (DMFBs) platform, and many methods have been developed to reduce the time and reagent usage associated with on-chip sample preparation. However, errors in fluidic operations can result in the concentration of the resulting droplet being outside the calibration range. Current error-recovery methods have the drawback that they need the use of on-chip sensors and further re-execution time. In this paper, we present two dilution-chain structures that can generate a droplet with a desired concentration even if volume variations occur during droplet splitting. Experimental results show the effectiveness of the proposed method compared to previous methods.