Numerical optimization of microfluidic biosensor detection time for the SARS-CoV-2 using the Taguchi method

Ibrahim Ben Mariem; Sameh Kaziz; Maissa Belkhiria; Fraj Echouchene; Hafedh Belmabrouk

doi:10.1007/s12648-023-02632-z

Numerical optimization of microfluidic biosensor detection time for the SARS-CoV-2 using the Taguchi method

Indian J Phys Proc Indian Assoc Cultiv Sci (2004). 2023 Mar 11:1-8. doi: 10.1007/s12648-023-02632-z. Online ahead of print.

Authors

Ibrahim Ben Mariem¹, Sameh Kaziz^{2

3}, Maissa Belkhiria¹, Fraj Echouchene^{1

4}, Hafedh Belmabrouk^{1

5}

Affiliations

¹ Electronic and Microelectronics Lab, Department of Physics, Faculty of Science of Monastir, University of Monastir, 5019 Monastir, Tunisia.
² Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia.
³ Higher National Engineering School of Tunis, Taha Hussein Montfleury Boulevard, University of Tunis, 1008 Tunis, Tunisia.
⁴ Higher Institute of Applied Sciences and Technology of Soussse, University of Sousse, Sousse, Tunisia.
⁵ Department of Physics, College of Science at Zulfi, Majmaah University, Al Majma'ah, 11952 Saudi Arabia.

Abstract

The performance of microfluidic biosensor of the SARS-Cov-2 was numerically analyzed through finite element method. The calculation results have been validated with comparison with experimental data reported in the literature. The novelty of this study is the use of the Taguchi method in the optimization analysis, and an L8(2⁵) orthogonal table of five critical parameters-Reynolds number (Re), Damköhler number (Da), relative adsorption capacity (σ), equilibrium dissociation constant (K_D), and Schmidt number (Sc), with two levels was designed. ANOVA methods are used to obtain the significance of key parameters. The optimal combination of the key parameters is Re = 10^-2, Da = 1000, σ = 0.2, K_D = 5, and Sc 10⁴ to achieve the minimum response time (0.15). Among the selected key parameters, the relative adsorption capacity (σ) has the highest contribution (42.17%) to the reduction of the response time, while the Schmidt number (Sc) has the lowest contribution (5.19%). The presented simulation results are useful in designing microfluidic biosensors in order to reduce their response time.

Keywords: ANOVA; Biosensor; Detection time; SARS-CoV-2; Taguchi method.

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