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微流控生物传感器中蛋白质检测的腔室填充的 CFD 建模。

CFD Modeling of Chamber Filling in a Micro-Biosensor for Protein Detection.

机构信息

Department of Chemical Engineering, Nazarbayev University, Astana 010000, Kazakhstan.

Graduate Program in Science, Engineering, and Technology & National Laboratory Astana, Nazarbayev University, Astana 010000, Kazakhstan.

出版信息

Biosensors (Basel). 2017 Oct 3;7(4):45. doi: 10.3390/bios7040045.

DOI:10.3390/bios7040045
PMID:28972568
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5746768/
Abstract

Tuberculosis (TB) remains one of the main causes of human death around the globe. The mortality rate for patients infected with active TB goes beyond 50% when not diagnosed. Rapid and accurate diagnostics coupled with further prompt treatment of the disease is the cornerstone for controlling TB outbreaks. To reduce this burden, the existing gap between detection and treatment must be addressed, and dedicated diagnostic tools such as biosensors should be developed. A biosensor is a sensing micro-device that consists of a biological sensing element and a transducer part to produce signals in proportion to quantitative information about the binding event. The micro-biosensor cell considered in this investigation is designed to operate based on aptamers as recognition elements against secreted protein MPT64, combined in a microfluidic-chamber with inlet and outlet connections. The microfluidic cell is a miniaturized platform with valuable advantages such as low cost of analysis with low reagent consumption, reduced sample volume, and shortened processing time with enhanced analytical capability. The main purpose of this study is to assess the flooding characteristics of the encapsulated microfluidic cell of an existing micro-biosensor using Computational Fluid Dynamics (CFD) techniques. The main challenge in the design of the microfluidic cell lies in the extraction of entrained air bubbles, which may remain after the filling process is completed, dramatically affecting the performance of the sensing element. In this work, a CFD model was developed on the platform ANSYS-CFX using the finite volume method to discretize the domain and solving the Navier-Stokes equations for both air and water in a Eulerian framework. Second-order space discretization scheme and second-order Euler Backward time discretization were used in the numerical treatment of the equations. For a given inlet-outlet diameter and dimensions of an in-house built cell chamber, different inlet liquid flow rates were explored to determine an appropriate flow condition to guarantee an effective venting of the air while filling the chamber. The numerical model depicted free surface waves as promoters of air entrainment that ultimately may explain the significant amount of air content in the chamber observed in preliminary tests after the filling process is completed. Results demonstrated that for the present design, against the intuition, the chamber must be filled with liquid at a modest flow rate to minimize free surface waviness during the flooding stage of the chamber.

摘要

结核病(TB)仍然是全球人类死亡的主要原因之一。未被诊断的活动性结核病患者的死亡率超过 50%。快速准确的诊断加上对疾病的进一步及时治疗,是控制结核病爆发的基石。为了减轻这一负担,必须解决检测和治疗之间现有的差距,并开发专门的诊断工具,如生物传感器。生物传感器是一种由生物传感元件和换能器部分组成的传感微器件,用于根据结合事件的定量信息产生比例信号。本研究中考虑的微生物传感器单元设计基于适体作为识别元件,针对分泌蛋白 MPT64,结合在带有进出口连接的微流控室内。微流控细胞是一种具有成本效益的平台,具有许多优势,如低试剂消耗的低成本分析、减少样品量、缩短处理时间和增强分析能力。本研究的主要目的是使用计算流体动力学(CFD)技术评估现有微生物传感器的封装微流控单元的淹没特性。微流控单元设计的主要挑战在于提取包封过程完成后可能残留的夹带气泡,这会极大地影响传感元件的性能。在这项工作中,在 ANSYS-CFX 平台上使用有限体积法开发了一个 CFD 模型,以离散域并在欧拉框架内求解空气和水的纳维-斯托克斯方程。在方程的数值处理中使用了二阶空间离散化方案和二阶欧拉向后时间离散化方案。对于给定的进出口直径和内部建造的单元室尺寸,探索了不同的进口液体流速,以确定合适的流动条件,以保证在填充腔室时有效地排出空气。数值模型描绘了自由表面波作为夹带空气的促进剂,这最终可以解释在填充过程完成后初步测试中观察到的腔室内大量空气含量。结果表明,对于目前的设计,与直觉相反,在腔室充满液体时,必须以适度的流速填充,以最小化腔室充满阶段的自由表面波动。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/948b/5746768/38854557f3b0/biosensors-07-00045-g014.jpg
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