To combat the coronavirus disease 2019 (COVID-19), great efforts have been made by scientists around the world to improve the performance of detection devices so that they can efficiently and quickly detect the virus responsible for this disease. In this context we performed 2D finite element simulation on the kinetics of SARS-CoV-2 S protein binding reaction of a biosensor using the alternating current electrothermal (ACET) effect. The ACET flow can produce vortex patterns, thereby improving the transportation of the target analyte to the binding surface and thus enhancing the performance of the biosensor. Optimization of some design parameters concerning the microchannel height and the reaction surface, such as its length as well as its position on the top wall of the microchannel, in order to improve the biosensor efficiency, was studied. The results revealed that the detection time can be improved by 55% with an applied voltage of 10 V rms and an operating frequency of 150 kHz and that the decrease in the height of the microchannel and in the length of the binding surface can lead to an increase in the rate of the binding reaction and therefore decrease the biosensor response time. Also, moving the sensitive surface from an optimal position, located in front of the electrodes, decreases the performance of the device.

A threshold-voltage-based 2-D theoretical model for the Current–Voltage characteristics of the AlGaN/GaN high electron mobility transistors (HEMT’s) is developed. The present work proposes an improved charge-control model by employing the Robin boundary condition when introduced the solution of the 2-D Poisson’s equation in the density of charge depleted in the AlGaN layer. The dependence of 2-DEG sheet carrier concentration on the aluminum composition and AlGaN layer thickness has been investigated in detail. Current–voltage characteristics developed from the 2-DEG model in order to take into account the impact of gate lengths. The relation between the kink effect and existing deep centers has also been confirmed by using an electrical approach, which can allow to adjust some of electron transport parameters in order to optimize the output current

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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 L8 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 10 5 , 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%).