A Droplet Clustering and Residue Removal Technique for Cross-contamination Avoidance in Digital Microfluidic Biochip

Abstract

Progressive research on design automation of digital microfluidic biochip is helping biochips to emerge as an effective alternative for several pathological experiments in the laboratories. This is often deployed for multiplexing several bioassays under optimized space and time constraints. We refer the droplets associated with bioassay of sample or reagents as serviceable droplets. During these assay operations the electrodes often endure multiple utilizations to provide a time optimized routing schedule. Here the residue left by one biomolecule may contaminate the serviceable droplets used in the subsequent assays. Minimization of such cross-contaminations under the strict adherence of time is an important aspect of research on design automation of digital microfluidic biochip. In this paper, a time optimized routing scheme has been proposed through clustering of routing areas for different serviceable droplets by area analysis. This method helps to reduce both intra and inter sub-problem cross-contamination. In this method, the droplet traces belonging to different subproblems are partitioned into some regions to produce a contamination minimized routing schedule. This technique effectively keeps track of cross-contamination factors between two successive sub-problems. However the method cannot totally eliminate the possibilities of cross-contamination among multiple sub-problems. Thus residue removal through rinsing of selective electrodes is still required where contamination can’t be avoided. Accordingly a time optimized residue removal operation has been proposed for intersecting electrodes through wash droplet scheduling. Experimental study of the proposed technique shows better result over some standard algorithms.