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

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 (<i>Re</i>), Damköhler number (<i>Da</i>), relative adsorption capacity (<i>σ</i>), equilibrium dissociation constant (<i>K</i>_<i>D</i>), and Schmidt number (<i>Sc</i>), with two levels was designed. ANOVA methods are used to obtain the significance of key parameters. The optimal combination of the key parameters is <i>Re</i> = 10^-2, <i>Da</i> = 1000, <i>σ</i> = 0.2, <i>K</i>_<i>D</i> = 5, and <i>Sc</i> 10⁴ to achieve the minimum response time (0.15). Among the selected key parameters, the relative adsorption capacity (<i>σ</i>) has the highest contribution (42.17%) to the reduction of the response time, while the Schmidt number (<i>Sc</i>) has the lowest contribution (5.19%). The presented simulation results are useful in designing microfluidic biosensors in order to reduce their response time.