Simulation of the Slip Velocity Effect in an AC Electrothermal Micropump

Numerical simulation and optimization of AC electrothermal microfluidic biosensor for COVID-19 detection through Taguchi method and artificial network

Microfluidic biosensors have played an important and challenging role for the rapid detection of the new severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Previous studies have shown that the kinetic binding reaction of the target antigen is strongly affected by process parameters. The purpose of this research was to optimize the performance of a microfluidic biosensor using two different approaches: Taguchi optimization and artificial neural network (ANN) optimization. Taguchi L8(2⁵) orthogonal array involving eight groups of experiments for five key parameters, which are microchannel shape, biosensor position, applied alternating current voltage, adsorption constant, and average inlet flow velocity, at two levels each, are performed to minimize the detection time of a biosensor excited by an alternating current electrothermal force. Signal to noise ratio ( S / N ) and analysis of variance were used to reach the optimal levels of process parameters and to demonstrate their percentage contributions, in terms of improved device response time. The principal results of this study showed that the Taguchi method was able to identify that the kinetic adsorption rate is the most influential parameter at 93% contribution, and the reaction surface position is the least influential parameter at 0.07% contribution. Also, the ANN model was able to accurately predict the optimal input values with a very low prediction error. Overall, the major conclusion of this study is both the Taguchi and ANN approaches can be effectively utilized to optimize the performance of a microfluidic biosensor. These advances have the potential to revolutionize the field of biosensing.

Taguchi method: artificial neural network approach for the optimization of high-efficiency microfluidic biosensor for COVID-19

COVID-19 is a pandemic disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This virus is mainly spread by droplets, respiratory secretions, and direct contact. Caused by the huge spread of the COVID-19 epidemic, research is focused on the study of biosensors as it presents a rapid solution for reducing incidents and fatality rates. In this paper, a microchip flow confinement method for the rapid transport of small sample volumes to sensor surfaces is optimized in terms of the confinement coefficient β, the position of the confinement flow X, and its inclination α relative to the main channel. A numerical simulation based on two-dimensional Navier-Stokes equations has been used. Taguchi's L₉(3³) orthogonal array was adopted to design the numerical assays taking into account the confining flow parameters (α, β, and X) on the response time of microfluidic biosensors. Analyzing the signal-to-noise ratio allowed us to determine the most effective combinations of control parameters for reducing the response time. The contribution of the control factors to the detection time was determined via analysis of variance (ANOVA). Numerical predictive models using multiple linear regression (MLR) and an artificial neural network (ANN) were developed to accurately predict microfluidic biosensor response time. This study concludes that the best combination of control factors is α 3 β 3 X 2 that corresponds to α = 90 ∘ , β = 25 and X = 40 µm. Analysis of variance (ANOVA) shows that the position of the confinement channel (62% contribution) is the factor most responsible for the reduction in response time. Based on the correlation coefficient (R ²), and value adjustment factor (VAF), the ANN model performed better than the MLR model in terms of prediction accuracy.

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Analysis of Temperature-Jump Boundary Conditions on Heat Transfer for Heterogeneous Microfluidic Immunosensors

The objective of the current study is to analyze numerically the effect of the temperature-jump boundary condition on heterogeneous microfluidic immunosensors under electrothermal force. A three-dimensional simulation using the finite element method on the binding reaction kinetics of C-reactive protein (CRP) was performed. The kinetic reaction rate was calculated with coupled Laplace, Navier−Stokes, energy, and mass diffusion equations. Two types of reaction surfaces were studied: one in the form of a disc surrounded by two electrodes and the other in the form of a circular ring, one electrode is located inside the ring and the other outside. The numerical results reveal that the performance of a microfluidic biosensor is enhanced by using the second design of the sensing area (circular ring) coupled with the electrothermal force. The improvement factor under the applied ac field 15 V_rms was about 1.2 for the first geometry and 3.6 for the second geometry. Furthermore, the effect of temperature jump on heat transfer rise and response time was studied. The effect of two crucial parameters, viz. Knudsen number (Kn) and thermal accommodation coefficient (σ_T) with and without electrothermal effect, were analyzed for the two configurations.

Enhancement of Heterogeneous Microfluidic Immunosensors Using New Sensing Area Shape with Electrothermal Effect

In heterogeneous microfluidic immunosensors, the diffusion boundary layer produced on the sensing area represents a critical factor that limits the biosensor performance. A three-dimensional simulation using the finite element method on the binding reaction kinetics of C-reactive protein (CRP) has been performed. We present a new microfluidic biosensor based on a novel reaction-surface design without and with electrothermal force. Two reaction surface configurations were studied. The kinetic reaction rate was calculated with coupled Navier−Stokes, mass diffusion, energy, and Laplace equations. The numerical results reveal that the characteristics of a microfluidic biosensor are more enhanced by using the circular ring design of the sensing area coupled with the electrothermal force. The rate of initial slope related to the association phase is multiplied by a factor 2 when the voltage is increased from 10 to 15 V. The results prove to be valuable in designing new microfluidic biosensors.