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Biosensors 2017, 7(4), 45; doi:10.3390/bios7040045

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

1
Department of Chemical Engineering, Nazarbayev University, Astana 010000, Kazakhstan
2
Graduate Program in Science, Engineering, and Technology & National Laboratory Astana, Nazarbayev University, Astana 010000, Kazakhstan
3
Department of Biology, School of Science and Technology, Nazarbayev University, Astana 010000, Kazakhstan
4
Department of Mechanical Engineering, Nazarbayev University, Astana 010000, Kazakhstan
*
Author to whom correspondence should be addressed.
Received: 31 July 2017 / Revised: 6 September 2017 / Accepted: 12 September 2017 / Published: 3 October 2017
(This article belongs to the Special Issue Point-of-Care Diagnostics)
View Full-Text   |   Download PDF [3387 KB, uploaded 26 October 2017]   |  

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 Mycobacterium tuberculosis 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. View Full-Text
Keywords: tuberculosis; biosensor; microfluidic cell; multiphase flow; Computational Fluid Dynamics (CFD); ANSYS-CFX tuberculosis; biosensor; microfluidic cell; multiphase flow; Computational Fluid Dynamics (CFD); ANSYS-CFX
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Islamov, M.; Sypabekova, M.; Kanayeva, D.; Rojas-Solórzano, L. CFD Modeling of Chamber Filling in a Micro-Biosensor for Protein Detection. Biosensors 2017, 7, 45.

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