Taguchi optimization of integrated flow microfluidic biosensor for COVID-19 detection

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

doi:10.1140/epjp/s13360-022-03457-1

Taguchi optimization of integrated flow microfluidic biosensor for COVID-19 detection

Eur Phys J Plus. 2022;137(11):1235. doi: 10.1140/epjp/s13360-022-03457-1. Epub 2022 Nov 12.

Authors

Sameh Kaziz^{1

2}, Ibrahim Ben Mariem¹, Fraj Echouchene^{3

4}, Maissa Belkhiria³, Hafedh Belmabrouk⁵

Affiliations

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

Abstract

In this research, Taguchi's method was employed to optimize the performance of a microfluidic biosensor with an integrated flow confinement for rapid detection of the SARS-CoV-2. The finite element method was used to solve the physical model which has been first validated by comparison with experimental results. The novelty of this study is the use of the Taguchi approach in the optimization analysis. An $L 8 (2^{7})$ orthogonal array of seven critical parameters-Reynolds number (Re), Damköhler number (Da), relative adsorption capacity ( $σ$ ), equilibrium dissociation constant (K_D), Schmidt number (Sc), confinement coefficient (α) and dimensionless confinement position (X), with two levels was designed. Analysis of variance (ANOVA) methods are also used to calculate the contribution of each parameter. The optimal combination of these key parameters was Re = 10^-2, Da = 1000, $σ$ = 0.5, K _D = 5, Sc = 10⁵, α = 2 and X = 2 to achieve the lowest dimensionless response time (0.11). Among the all-optimization factors, the relative adsorption capacity ( $σ$ ) has the highest contribution (37%) to the reduction of the response time, while the Schmidt number (Sc) has the lowest contribution (7%).

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