simop -一个快速工具,用于生成最佳稀释的微流控样品使用模拟

Sutirtha Das, S. Mukherjee, Neha Aryani, S. Majumder, N. Bera, B. Bhattacharya
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引用次数: 2

摘要

数字微流控(DMF)生物芯片技术现在提供了可行的替代昂贵的医疗保健和生物,化学实验室程序与低成本,全自动,小型化集成系统。制备流体样品的稀释,以优化各种参数,如试剂成本、混合时间、浪费产生,是算法微流体领域的一个基本问题。大多数现有的基于微流控系统的稀释算法采用(1:1)混合分离步骤,其中两个单位体积不同浓度的液滴混合,然后进行平衡分离操作以获得两个大小相等的液滴。在本文中,我们介绍了一种模拟指导优化程序(SIMOP),用于通过一系列(1:1)混合分割步骤来实现目标浓度,同时根据用户指定的优先级优化多个因素。simop算法产生给定的浓度,同时根据需要优化每个标准。实验结果表明,与BS和DMRW算法相比,该方法具有良好的性能。该方法在生物医学工程和医疗保健服务等微流体领域具有广泛的应用前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SIMOP-A fast tool for generating optimum dilutions of microfluidic samples using simulation
The technology of digital microfluidic (DMF) biochips now offers viable replacement of expensive healthcare and bio-, chemical laboratory procedures with low-cost, fully-automated, miniaturized integrated systems. Preparing dilution of a fluid sample that optimizes various parameters such as reagent-cost, mixing time, waste production, is a basic problem in the domain of algorithmic microfluidics. Most of the existing dilution algorithms used in droplet-based microfluidic systems deploy a sequence of (1 : 1) mix-split steps, where two unit-volume droplets of different concentrations are mixed, followed by a balanced split operation to obtain two equal-sized droplets. In this paper, we introduce a simulation-guided optimization procedure (SIMOP) for achieving the target concentrations with a sequence of (1 : 1) mix-split steps while optimizing multiple factors according to user-specified priority levels. The SIMOP-algorithm produces a given concentration while optimizing each criterion as desired. Experimental results favorably demonstrate the performance of the proposed method compared to BS and DMRW algorithms. The proposed procedure may find many potential applications to microfluidics such as in' biomedical engineering and healthcare services.
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