Zagklavara, F, Jimack, PK, Kapur, N et al. (2 more authors) (2021) Optimisation of microfluidic polymerase chain reaction devices. In: International Conference on Computational Heat, Mass and Momentum Transfer (ICCHMT 2021), 18-19 May 2021, Online.
Abstract
<jats:p>The invention and development of Polymerase Chain Reaction (PCR) technology have revolutionised molecular biology and molecular diagnostics. There is an urgent need to optimise the performance of these devices while reducing the total construction and operation costs. This study proposes a CFD-enabled optimisation methodology for continuous flow (CF) PCR devices with serpentine-channel structure, which enables the optimisation of DNA amplification efficiency and pressure drop to be explored while varying the width (W) and height (H) of the microfluidic (μ) channel. This is achieved by using a surrogate-enabled optimisation approach accounting for the geometrical features of a μCFPCR device by performing a series of simulations using COMSOL Multiphysics 5.4<jats:sup>®</jats:sup>. The values of the objectives are extracted from the CFD solutions, and the response surfaces are created using polyharmonic splines. Genetic algorithms are then used to locate the optimum design parameters. The results indicate that there is the possibility of improving the DNA concentration and the pressure drop in a PCR cycle by ~2.1 % ([W, H] = [400 μm, 50 μm]) and ~95.2 % ([W, H] = [400 μm, 80 μm]) respectively, by modifying its geometry.</jats:p>
Metadata
Item Type: | Conference or Workshop Item |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Authors, published by EDP Sciences, 2021. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 17 Jan 2022 17:13 |
Last Modified: | 17 Jan 2022 17:13 |
Status: | Published |
Publisher: | EDP Sciences |
Identification Number: | 10.1051/e3sconf/202132101007 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:182348 |