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Xenakis A, Ruiz-Soler A, Keshmiri A. Multi-Objective Optimisation of a Novel Bypass Graft with a Spiral Ridge. Bioengineering (Basel) 2023; 10:bioengineering10040489. [PMID: 37106676 PMCID: PMC10136357 DOI: 10.3390/bioengineering10040489] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 04/04/2023] [Accepted: 04/18/2023] [Indexed: 04/29/2023] Open
Abstract
The low long-term patency of bypass grafts is a major concern for cardiovascular treatments. Unfavourable haemodynamic conditions in the proximity of distal anastomosis are closely related to thrombus creation and lumen lesions. Modern graft designs address this unfavourable haemodynamic environment with the introduction of a helical component in the flow field, either by means of out-of-plane helicity graft geometry or a spiral ridge. While the latter has been found to lack in performance when compared to the out-of-plane helicity designs, recent findings support the idea that the existing spiral ridge grafts can be further improved in performance through optimising relevant design parameters. In the current study, robust multi-objective optimisation techniques are implemented, covering a wide range of possible designs coupled with proven and well validated computational fluid dynamics (CFD) algorithms. It is shown that the final set of suggested design parameters could significantly improve haemodynamic performance and therefore could be used to enhance the design of spiral ridge bypass grafts.
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Affiliation(s)
- Antonios Xenakis
- School of Engineering, The University of Manchester, Manchester M13 9PL, UK
| | - Andres Ruiz-Soler
- School of Engineering, The University of Manchester, Manchester M13 9PL, UK
| | - Amir Keshmiri
- School of Engineering, The University of Manchester, Manchester M13 9PL, UK
- Department of Cardiothoracic Surgery, Manchester University NHS Foundation Trust, Manchester M13 9WL, UK
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2
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Ben Mariem I, Kaziz S, Belkhiria M, Echouchene F, Belmabrouk H. Numerical optimization of microfluidic biosensor detection time for the SARS-CoV-2 using the Taguchi method. INDIAN JOURNAL OF PHYSICS AND PROCEEDINGS OF THE INDIAN ASSOCIATION FOR THE CULTIVATION OF SCIENCE (2004) 2023; 97:1-8. [PMID: 37361718 PMCID: PMC10008012 DOI: 10.1007/s12648-023-02632-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 02/06/2023] [Indexed: 05/20/2023]
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 (Re), Damköhler number (Da), relative adsorption capacity (σ), equilibrium dissociation constant (KD), and Schmidt number (Sc), with two levels was designed. ANOVA methods are used to obtain the significance of key parameters. The optimal combination of the key parameters is Re = 10-2, Da = 1000, σ = 0.2, KD = 5, and Sc 104 to achieve the minimum response time (0.15). Among the selected key parameters, the relative adsorption capacity (σ) has the highest contribution (42.17%) to the reduction of the response time, while the Schmidt number (Sc) has the lowest contribution (5.19%). The presented simulation results are useful in designing microfluidic biosensors in order to reduce their response time.
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Affiliation(s)
- Ibrahim Ben Mariem
- Electronic and Microelectronics Lab, Department of Physics, 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, Environment Boulevard, 5019 Monastir, Tunisia
- Higher National Engineering School of Tunis, Taha Hussein Montfleury Boulevard, University of Tunis, 1008 Tunis, Tunisia
| | - Maissa Belkhiria
- Electronic and Microelectronics Lab, Department of Physics, Faculty of Science of Monastir, University of Monastir, 5019 Monastir, Tunisia
| | - Fraj Echouchene
- Electronic and Microelectronics Lab, Department of Physics, Faculty of Science of Monastir, University of Monastir, 5019 Monastir, Tunisia
- Higher Institute of Applied Sciences and Technology of Soussse, University of Sousse, Sousse, Tunisia
| | - Hafedh Belmabrouk
- Electronic and Microelectronics Lab, Department of Physics, Faculty of Science of Monastir, University of Monastir, 5019 Monastir, Tunisia
- Department of Physics, College of Science at Zulfi, Majmaah University, Al Majma’ah, 11952 Saudi Arabia
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3
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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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4
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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 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. 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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Shahbazi F, Esfahani MN, Jabbari M, Keshmiri A. A Molecular Dynamics Model for Biomedical Sensor Evaluation: Nanoscale Numerical Simulation of an Aluminum-Based Biosensor. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:613-616. [PMID: 36086108 DOI: 10.1109/embc48229.2022.9871498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Metallic nanostructured-based biosensors provide label-free, multiplexed, and real-time detections of chemical and biological targets. Aluminum-based biosensors are favored in this category, due to their enhanced stability and profitability. Despite the recent advances in nanotechnology and the significant improvement in development of these biosensors, some deficiencies restrict their utilization. Hence a detailed insight into their behavior in different conditions would be crucial, which can be achieved with nanoscale numerical simulation. With this aim, an Aluminum-based biosensor is chosen to be analyzed with the help of all-atom molecular dynamics model (AA-MD), using large-scale atomic/molecular massively parallel simulator (LAMMPS). The surface properties and adsorption process through different flow conditions and various concentration of the target, are investigated in this study. In the future work, the results of this study will be used for developing a predictive model for surface properties of the biosensor. Clinical Relevance- The role of biosensors in clinical applications and early diagnosis is evident. This work provides a model for predicting the binding behavior of the target molecules on the biosensor surface in different conditions. Results demonstrate an increase in the adsorption of ethanol on the biosensor surface of 7% up to 80% with changing the velocity from 0.001 m/s to 1 m/s Although for cases with higher concentration this trend becomes complicated necessitating the implementation of machine learning models in the future works.
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Mohamadi F, Fazeli A. A Review on Applications of CFD Modeling in COVID-19 Pandemic. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING : STATE OF THE ART REVIEWS 2022; 29:3567-3586. [PMID: 35079217 PMCID: PMC8773396 DOI: 10.1007/s11831-021-09706-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 12/28/2021] [Indexed: 05/25/2023]
Abstract
COVID-19 pandemic has started a big challenge to the world health and economy during recent years. Many efforts were made to use the computation fluid dynamic (CFD) approach in this pandemic. CFD was used to understanding the airborne dispersion and transmission of this virus in different situations and buildings. The effect of the different conditions of the ventilation was studied by the CFD modeling to discuss preventing the COVID-19 transmission. Social distancing and using the facial masks were also modeled by the CFD approach to study the effect on reducing dispersion of the microdroplets containing the virus. Most of these recent applications of the CFD were reviewed for COVID-19 in this article. Special applications of the CFD modeling such as COVID-19 microfluidic biosensors, and COVID-19 inactivation using UV radiation were also reviewed in this research. The main findings of each research were also summarized in a table to answer critical questions about the effectiveness levels of applying the COVID-19 health protocols. CFD applications for modeling of COVID-19 dispersion in an airplane cabin, an elevator, a small classroom, a supermarket, an operating room of a hospital, a restaurant, a hospital waiting room, and a children's recovery room in a hospital were discussed briefly in different scenarios. CFD modeling for studying the effect of social distancing with different spaces, using and not using facial masks, difference of sneezing and coughing, different inlet/outlet ventilation layouts, combining air-conditioning and sanitizing machine, and using general or local air-conditioning systems were reviewed.
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Affiliation(s)
- Fateme Mohamadi
- Department of Chemical Engineering, Caspian Faculty of Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Ali Fazeli
- Department of Chemical Engineering, Caspian Faculty of Engineering, College of Engineering, University of Tehran, Tehran, Iran
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7
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Kaziz S, Ben Mariem I, Echouchene F, Belkhiria M, Belmabrouk H. Taguchi optimization of integrated flow microfluidic biosensor for COVID-19 detection. EUROPEAN PHYSICAL JOURNAL PLUS 2022; 137:1235. [PMID: 36405040 PMCID: PMC9660129 DOI: 10.1140/epjp/s13360-022-03457-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Accepted: 10/17/2022] [Indexed: 05/20/2023]
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 (KD), 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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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
| | - Ibrahim Ben Mariem
- Quantum and Statistical Physics Laboratory, Faculty of Sciences 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 Sousse, University of Sousse, Sousse, Tunisia
| | - Maissa Belkhiria
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
| | - Hafedh Belmabrouk
- Department of Physics, College of Science at Zulfi, Majmaah University, Al Majma’ah, Saudi Arabia
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8
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Kaziz S, Ben Mariem I, Echouchene F, Gazzah MH, Belmabrouk H. Design parameters optimization of an electrothermal flow biosensor for the SARS-CoV-2 S protein immunoassay. INDIAN JOURNAL OF PHYSICS AND PROCEEDINGS OF THE INDIAN ASSOCIATION FOR THE CULTIVATION OF SCIENCE (2004) 2022; 96:4091-4101. [PMID: 35463477 PMCID: PMC9013635 DOI: 10.1007/s12648-022-02360-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 03/25/2022] [Indexed: 05/20/2023]
Abstract
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.
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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
| | - Ibrahim Ben Mariem
- Quantum and Statistical Physics Laboratory, Faculty of Sciences 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
| | - Mohamed Hichem Gazzah
- Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
| | - Hafedh Belmabrouk
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
- Department of Physics, College of Science at Al Zulfi, Majmaah University, Al Majma’ah, 11952 Saudi Arabia
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Kaziz S, Saad Y, Gazzah MH, Belmabrouk H. 3D simulation of microfluidic biosensor for SARS-CoV-2 S protein binding kinetics using new reaction surface design. EUROPEAN PHYSICAL JOURNAL PLUS 2022; 137:241. [PMID: 35194535 PMCID: PMC8854486 DOI: 10.1140/epjp/s13360-022-02470-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 02/10/2022] [Indexed: 05/05/2023]
Abstract
In this study, we performed 3D finite element simulations on the binding reaction kinetics of SARS-CoV-2 S protein (target analyte) and its corresponding immobilized antibody (ligand) in a heterogeneous microfluidic immunoassay. Two types of biosensors with two different shapes and geometries of the reaction surface and electrodes were studied. Alternating current electrothermal (ACET) force was applied to improve the binding efficiency of the biomolecular pairs by accelerating the transport of analytes to the binding surface. The ACET force stirs the flow field, thereby reducing the thickness of the diffusion boundary layer, often developed on the reaction surface due to the slow flow velocity, low analyte diffusion coefficient, and surface reaction high rate. The results showed that the detection time of one of the biosensors can be improved by 69% under an applied voltage of 10 Vrms and an operating frequency of 100 kHz. Certain control factors such as the thermal boundary conditions as well as the electrical conductivity of the buffer solution were analyzed in order to find the appropriate values to improve the efficiency of the biosensor.
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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
| | - Yosra Saad
- Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
| | - Mohamed Hichem Gazzah
- Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
| | - Hafedh Belmabrouk
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
- Department of Physics, College of Science at Al Zulfi, Majmaah University, Al Majmaah, 11952 Saudi Arabia
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Li R, Zhang M, Wu Y, Tang P, Sun G, Wang L, Mandal S, Wang L, Lang J, Passalacqua A, Subramaniam S, Song G. What We Are Learning from COVID-19 for Respiratory Protection: Contemporary and Emerging Issues. Polymers (Basel) 2021; 13:4165. [PMID: 34883668 PMCID: PMC8659889 DOI: 10.3390/polym13234165] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 11/23/2021] [Accepted: 11/24/2021] [Indexed: 02/07/2023] Open
Abstract
Infectious respiratory diseases such as the current COVID-19 have caused public health crises and interfered with social activity. Given the complexity of these novel infectious diseases, their dynamic nature, along with rapid changes in social and occupational environments, technology, and means of interpersonal interaction, respiratory protective devices (RPDs) play a crucial role in controlling infection, particularly for viruses like SARS-CoV-2 that have a high transmission rate, strong viability, multiple infection routes and mechanisms, and emerging new variants that could reduce the efficacy of existing vaccines. Evidence of asymptomatic and pre-symptomatic transmissions further highlights the importance of a universal adoption of RPDs. RPDs have substantially improved over the past 100 years due to advances in technology, materials, and medical knowledge. However, several issues still need to be addressed such as engineering performance, comfort, testing standards, compliance monitoring, and regulations, especially considering the recent emergence of pathogens with novel transmission characteristics. In this review, we summarize existing knowledge and understanding on respiratory infectious diseases and their protection, discuss the emerging issues that influence the resulting protective and comfort performance of the RPDs, and provide insights in the identified knowledge gaps and future directions with diverse perspectives.
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Affiliation(s)
- Rui Li
- Department of Apparel, Events, and Hospitality Management, Iowa State University, Ames, IA 50010, USA; (R.L.); (M.Z.); (Y.W.); (L.W.)
| | - Mengying Zhang
- Department of Apparel, Events, and Hospitality Management, Iowa State University, Ames, IA 50010, USA; (R.L.); (M.Z.); (Y.W.); (L.W.)
| | - Yulin Wu
- Department of Apparel, Events, and Hospitality Management, Iowa State University, Ames, IA 50010, USA; (R.L.); (M.Z.); (Y.W.); (L.W.)
| | - Peixin Tang
- Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA; (P.T.); (G.S.)
| | - Gang Sun
- Department of Biological and Agricultural Engineering, University of California, Davis, CA 95616, USA; (P.T.); (G.S.)
| | - Liwen Wang
- Department of Apparel, Events, and Hospitality Management, Iowa State University, Ames, IA 50010, USA; (R.L.); (M.Z.); (Y.W.); (L.W.)
| | - Sumit Mandal
- Department of Design, Housing and Merchandising, Oklahoma State University, Stillwater, OK 74078, USA;
| | - Lizhi Wang
- Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, IA 50010, USA;
| | - James Lang
- Department of Kinesiology, Iowa State University, Ames, IA 50010, USA;
| | - Alberto Passalacqua
- Department of Mechanical Engineering, Iowa State University, Ames, IA 50010, USA; (A.P.); (S.S.)
| | - Shankar Subramaniam
- Department of Mechanical Engineering, Iowa State University, Ames, IA 50010, USA; (A.P.); (S.S.)
| | - Guowen Song
- Department of Apparel, Events, and Hospitality Management, Iowa State University, Ames, IA 50010, USA; (R.L.); (M.Z.); (Y.W.); (L.W.)
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11
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Scientific Developments and New Technological Trajectories in Sensor Research. SENSORS 2021; 21:s21237803. [PMID: 34883807 PMCID: PMC8659793 DOI: 10.3390/s21237803] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/12/2021] [Accepted: 11/12/2021] [Indexed: 02/06/2023]
Abstract
Scientific developments and new technological trajectories in sensors play an important role in understanding technological and social change. The goal of this study is to develop a scientometric analysis (using scientific documents and patents) to explain the evolution of sensor research and new sensor technologies that are critical to science and society. Results suggest that new directions in sensor research are driving technological trajectories of wireless sensor networks, biosensors and wearable sensors. These findings can help scholars to clarify new paths of technological change in sensors and policymakers to allocate research funds towards research fields and sensor technologies that have a high potential of growth for generating a positive societal impact.
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12
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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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13
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Affiliation(s)
- Arben Merkoçi
- Nanobioelectronics & Biosensors Group, Catalan Institute of Nanoscience and Nanotechnology (ICN2), BIST, Campus UAB, 08193, Bellaterra, Barcelona, Spain; ICREA, Institució Catalana de Recerca I Estudis Avançats, Barcelona, Spain.
| | - Chen-Zhong Li
- Center of Cellular and Molecular Diagnosis, Tulane University School of Medicine, New Orleans, LA, 70112, USA.
| | - Laura M Lechuga
- Nanobiosensors and Bioanalytical Applications (NanoB2A), Catalan Institute of Nanoscience and Nanotechnology (ICN2), CSIC, BIST and CIBER-BBN, 08193, Bellaterra, Barcelona, Spain.
| | - Aydogan Ozcan
- Electrical & Computer Engineering and Bioengineering Departments, UCLA, Los Angeles, CA, 90095, USA.
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Kaziz S, Saad Y, Bouzid M, Selmi M, Belmabrouk H. Enhancement of COVID-19 detection time by means of electrothermal force. MICROFLUIDICS AND NANOFLUIDICS 2021; 25:86. [PMID: 34548854 PMCID: PMC8446728 DOI: 10.1007/s10404-021-02490-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 09/05/2021] [Indexed: 05/04/2023]
Abstract
The rapid spread and quick transmission of the new ongoing pandemic coronavirus disease 2019 (COVID-19) has urged the scientific community to looking for strong technology to understand its pathogenicity, transmission, and infectivity, which helps in the development of effective vaccines and therapies. Furthermore, there was a great effort to improve the performance of biosensors so that they can detect the pathogenic virus quickly, in reliable and precise way. In this context, we propose a numerical simulation to highlight the important role of the design parameters that can significantly improve the performance of the biosensor, in particular the sensitivity as well as the detection limit. Applied alternating current electrothermal (ACET) force can generate swirling patterns in the fluid within the microfluidic channel, which improve the transport of target molecule toward the reaction surface and, thus, enhance the response time of the biosensor. In this work, the ACET effect on the SARS-CoV-2 S protein binding reaction kinetics and on the detection time of the biosensor was analyzed. Appropriate choice of electrodes location on the walls of the microchannel and suitable values of the dissociation and association rates of the binding reaction, while maintaining the same affinity, with and without ACET effect, are also, discussed to enhance the total performance of the biosensor and reduce its response time. The two-dimensional equations system is solved by the finite element approach. The best performance of the biosensor is obtained in the case where the response time decreased by 61% with AC applying voltage.
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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
| | - Yosra Saad
- Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
| | - Mohamed Bouzid
- Quantum and Statistical Physics Laboratory, Faculty of Sciences of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
| | - Marwa Selmi
- Department of Radiological Sciences and Medical Imaging, College of Applied Medical Sciences, Majmaah University, AlMajmaah, 11952 Saudi Arabia
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
| | - Hafedh Belmabrouk
- Laboratory of Electronics and Microelectronics, Faculty of Science of Monastir, University of Monastir, Environment Boulevard, 5019 Monastir, Tunisia
- Department of Physics, College of Science at Al Zulfi, Majmaah University, AlMajmaah, Saudi Arabia
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Shahbazi F, Jabbari M, Esfahani MN, Keshmiri A. Numerical framework for simulating bio-species transport in microfluidic channels with application to antibody biosensors. MethodsX 2020; 7:101132. [PMID: 33251124 PMCID: PMC7679250 DOI: 10.1016/j.mex.2020.101132] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2020] [Accepted: 11/01/2020] [Indexed: 11/09/2022] Open
Abstract
Diagnosis is a fundamental stage in health care and medical treatment. Microfluidic biosensors and lab-on-a-chip devices are amongst the few practical tools for achieving this goal. A new computational code, specifically for designing microfluidic-integrated biosensors is developed, the details of which is presented in this work. This new approach is developed using control-volume based finite-element (CVFEM) method and solves bio-recognition chemical reactions and full Navier–Stokes equations. The results of the proposed platform are validated against the experimental data for a microfluidic based biosensor, where excellent agreement is achieved. The properties of the biosensor, sample, buffer fluid and even the microfluidic channel can easily be modified in this platform. This feature provides the scientific community with the ability to design a specific biosensor for requested point-of-care applications.A new approach is developed using control-volume based finite-element (CVFEM) method for investigating flow inside a microfluidic-integrated biosensor. It is also used to study the influence of surface functionalization on binding cycle. The proposed model solves bio-recognition chemical reactions as well as full Navier–Stokes and energy equations. Experimental-based or personalized equations of the chemical reactions and flow behaviour are adoptable to this code. The developed model is Fortran-based and has the potential to be used in both industry and academia for biosensing technology.
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Affiliation(s)
- Fatemeh Shahbazi
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester M13 9PL, UK
| | - Masoud Jabbari
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester M13 9PL, UK
| | | | - Amir Keshmiri
- Department of Mechanical, Aerospace and Civil Engineering, University of Manchester, Manchester M13 9PL, UK.,Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Southmoor Road, Wythenshawe, Manchester M13 9PL, UK
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