Multi-target Fluid Mixing in MEDA Biochips: Theory and an Attempt toward Waste Minimization

Abstract

Sample preparation is an inherent procedure of many biochemical applications, and digital microfluidic biochips (DMBs) have proved to be very effective in performing such a procedure. In a single mixing step, conventional DMBs can mix two droplets in a 1:1 ratio only. Due to this limitation, DMBs suffer from heavy fluid wastage and often require a lot of mixing steps. However, the next-generation DMBs, i.e., micro-electrode-dot-array (MEDA) biochips, can realize multiple mixing ratios, which in general helps in minimizing the number of mixing operations. In this article, we present a heuristic-based sample preparation algorithm, specifically a mixing algorithm called Division by Factor Method for MEDA that exploits the mixing models of MEDA biochips. We propose another mixing algorithm for MEDA biochips called Single Target Waste Minimization ( STWM ), which minimizes the wastage of fluids and determines an efficient mixing graph. We also propose an advanced methodology for multiple target reagent mixing problems called Multi-target Waste Minimization ( MTWM ), which determines efficient mixing graphs for different target ratios by maximizing the sharing of fluids and minimizing the fluid wastage. Simulation results suggest that the proposed STWM and MTWM methods outperform the state-of-the-art methods in terms of minimizing the amount of fluid wastage, reducing the total usage of reagent fluids, and minimizing the number of mixing operations.