Multi-Target Fluid Mixing in MEDA Biochips: Theory and an Attempt towards Waste Minimization

IF 2.8 4区 计算机科学 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Debraj Kundu, Sudip Roy
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引用次数: 0

Abstract

Sample preparation is an inherent procedure of many biochemical applications, and digital microfluidic biochips (DMBs) proved to be very effective in performing such a procedure. In a single mixing step, conventional DMBs can mix two droplets in 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 paper, 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.
MEDA生物芯片中多目标流体混合:最小化浪费的理论与尝试
样品制备是许多生物化学应用的固有过程,数字微流控生物芯片(DMBs)被证明在执行这种过程中非常有效。在单个混合步骤中,传统DMB只能以1:1的比例混合两个液滴。由于这种限制,DMB遭受严重的流体浪费,并且通常需要大量的混合步骤。然而,下一代DMB,即微电极点阵列(MEDA)生物芯片,可以实现多种混合比,这通常有助于最大限度地减少混合操作的次数。在本文中,我们提出了一种基于启发式的样品制备算法,特别是一种称为MEDA因子除法的混合算法,该算法利用了MEDA生物芯片的混合模型。我们为MEDA生物芯片提出了另一种混合算法,称为单目标废物最小化(STWM),该算法最大限度地减少了流体的浪费,并确定了有效的混合图。我们还提出了一种用于多目标试剂混合问题的高级方法,称为多目标废物最小化(MTWM),该方法通过最大化流体共享和最小化流体浪费来确定不同目标比例的有效混合图。仿真结果表明,所提出的STWM和MTWM方法在最小化流体浪费量、减少试剂流体的总使用量和最小化混合操作次数方面优于最先进的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACM Transactions on Design Automation of Electronic Systems
ACM Transactions on Design Automation of Electronic Systems 工程技术-计算机:软件工程
CiteScore
3.20
自引率
7.10%
发文量
105
审稿时长
3 months
期刊介绍: TODAES is a premier ACM journal in design and automation of electronic systems. It publishes innovative work documenting significant research and development advances on the specification, design, analysis, simulation, testing, and evaluation of electronic systems, emphasizing a computer science/engineering orientation. Both theoretical analysis and practical solutions are welcome.
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