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Ben Romdhane I, Jemmali A, Kaziz S, Echouchene F, Alshahrani T, Belmabrouk H. Taguchi method: artificial neural network approach for the optimization of high-efficiency microfluidic biosensor for COVID-19. EUROPEAN PHYSICAL JOURNAL PLUS 2023; 138:359. [PMID: 37131342 PMCID: PMC10132959 DOI: 10.1140/epjp/s13360-023-03988-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 04/12/2023] [Indexed: 05/04/2023]
Abstract
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 isα 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. Graphic abstract
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Affiliation(s)
- Imed Ben Romdhane
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, 5019 Monastir, Tunisia
| | - Asma Jemmali
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, 5019 Monastir, Tunisia
| | - Sameh Kaziz
- Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, 5019 Monastir, Tunisia
- Higher National Engineering School of Tunis, Taha Hussein Montfleury Boulevard, University of Tunis, 1008 Tunis, Tunisia
| | - Fraj Echouchene
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, 5019 Monastir, Tunisia
- Higher Institute of Applied Sciences and Technology of Sousse, Sousse, Tunisia
| | - Thamraa Alshahrani
- Department of Physics, College of Science, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia
| | - Hafedh Belmabrouk
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, 5019 Monastir, Tunisia
- Department of Physics, College of Science, Majmaah University, Al Majma’ah, 11952 Saudi Arabia
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Kaziz S, Ben Romdhane I, Echouchene F, Gazzah MH. Numerical simulation and optimization of AC electrothermal microfluidic biosensor for COVID-19 detection through Taguchi method and artificial network. EUROPEAN PHYSICAL JOURNAL PLUS 2023; 138:96. [PMID: 36741917 PMCID: PMC9884486 DOI: 10.1140/epjp/s13360-023-03712-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 01/17/2023] [Indexed: 05/20/2023]
Abstract
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.
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Affiliation(s)
- Sameh Kaziz
- Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
- Higher National Engineering School of Tunis, Taha Hussein Montfleury Boulevard, University of Tunis, 1008 Tunis, Tunisia
| | - Imed Ben Romdhane
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
| | - Fraj Echouchene
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
- Higher Institute of Applied Sciences and Technology of Soussse, University of Sousse, Sousse, Tunisia
| | - Mohamed Hichem Gazzah
- Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
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Analysis of Temperature-Jump Boundary Conditions on Heat Transfer for Heterogeneous Microfluidic Immunosensors. SENSORS 2021; 21:s21103502. [PMID: 34069780 PMCID: PMC8157299 DOI: 10.3390/s21103502] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 01/13/2021] [Accepted: 01/28/2021] [Indexed: 12/20/2022]
Abstract
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 Vrms 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 (σT) with and without electrothermal effect, were analyzed for the two configurations.
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Enhancement of Heterogeneous Microfluidic Immunosensors Using New Sensing Area Shape with Electrothermal Effect. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11104566] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
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.
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