Two-level clustering-based techniques for intelligent droplet routing in digital microfluidic biochips

Current development of micro fabrication and microfluidic technology enables the digital microfluidic biochips (DMFB) to offer a platform for developing diagnostic applications with the advantages of portability, increased automation, low-power consumption, ease of mass manufacturing, and high throughput. A digital microfluidic system typically consists of a planar array of cells with electrodes that control individual droplets of biological samples. Chemical analysis is performed by moving, mixing, and splitting of droplets. A major issue in biochip layout design is the coordination of simultaneous movement of multiple droplets. It involves the scheduling of movement of a number of droplets in a time-multiplexed manner to avoid their cross-contamination. In this paper we propose a clustering technique to achieve routing of maximum number of samples from a given set of sub-problems in the same planar array with intelligent collision avoidance. A new cluster-based route-aware placement technique is also proposed that enhances the performance of droplet routing, accommodating larger number of concurrently routed sub-problems in the same planar array. The objectives considered are minimizing the latest arrival time of droplets, total routing time of droplets and the overall cell utilization. Experimental simulation results obtained using testbenches for benchmark suite III are found to be better than the recent existing works.

► This work is related with design automation of DMFBs.
► The technique aims at integration of multiple bioassays in a single array.
► A two level cluster based method is used to maximize number of samples in one DMFB.
► Placement constraints and module dependencies are evaluated for clustering. In the level II clustering rearrangement of nets are used to enhance optimization.
► The objective is to maximize number of bioassays in single DMFBs. The results show optimization in overall routing time and resource utilization.