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Designing Photonic Crystal Fibers incorporating the Surface Plasmon Resonance Phenomenon (PCF-SPR) has led to numerous interesting applications. This investigation presents an exceptionally responsive surface plasmon resonance sensor, seamlessly integrated into a dual-core photonic crystal fiber, specifically designed for low refractive index (RI) detection. The integration of a plasmonic material, namely silver (Ag), externally deposited on the fiber structure, facilitates real-time monitoring of variations in the refractive index of the surrounding medium. To ensure long-term functionality and prevent oxidation, a thin layer of titanium dioxide (TiO 2 ) covers the silver coating. To optimize the sensor, five key design parameters, including pitch, air hole diameter, and silver thickness, are fine-tuned using the Taguchi L 8 (2 5 ) orthogonal array. The optimal results obtained present spectral and amplitude sensitivities that reach remarkable values of 10,000 nm/RIU and 235,882 RIU-1, respectively. In addition, Artificial Neural Network (ANN) optimization techniques, specifically Multi-Layer Perceptron (MLP) and Particle Swarm Optimization (PSO), are used to predict a critical optical property of the sensor confinement loss (α loss ). These predictions are derived from the same input structure parameters that are present in the full L 32 (2 5 ) design experiment. A genetic algorithm (GA) is then applied for optimization with the goal of maximizing the confinement loss. Our results highlight the effectiveness of training PSO artificial neural networks and demonstrate their ability to quickly and accurately predict results for unknown geometric dimensions, demonstrating their significant potential in this innovative context. The proposed sensor design can be used for various applications including pharmaceutical inspection and detection of low refractive index analytes., (© 2024. The Author(s).)

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(2 5 ) orthogonal table of five critical parameters-Reynolds number ( Re ), Damköhler number ( Da ), relative adsorption capacity ( σ ), equilibrium dissociation constant ( K D ), 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, K D  = 5, and Sc 10 4 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., (© Indian Association for the Cultivation of Science 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

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(2 5 ) 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., (© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

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 L 9 (3 3 ) 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., Competing Interests: Conflict of interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

Partial discharge (PD) diagnosis tests, including detecting, locating, and identifying, are used to trace defects or faults and assess the degree of aging in order to monitor the insulation condition of medium- and high-voltage power cables. In this context, an experimental evaluation of three different printed circuit board (PCB)-based inductive sensor topologies, with spiral, non-spiral, and meander shapes, is performed. The aim is to assess their capabilities for PD detection along a transmission power cable. First, simulation and experimental characterization are carried out to determine the equivalent electrical circuit and the quality factor of the three sensors. PD activity was studied in the lab on a 10-m-long defective MVAC cable. The three PCB-based sensors were tested in three different positions: directly on the defective cable (P1), at a separation distance of 10 cm to 3 m (P2), and on the ground line (P3). For the three positions, all sensors' outputs present a damped sine wave signal with similar frequencies and durations. Experimental results showed that the best sensitivity was given by the non-spiral inductor, with a peak voltage of around 500 mV in P1, 428 mV in P2, and 45 mV in P3, while the meander sensor had the lowest values, which were approximately 80 mV in P1. The frequency spectrum bandwidth of all sensors was between 10 MHz and 45 MHz. The high sensitivity of the non-spiral inductor could be associated with its interesting properties in terms of quality factor and SFR, which are due to its very low resistivity. To benchmark the performance of the designed three-loop sensors, a comparison with a commercial high-frequency current transformer (HFCT) is also made., Competing Interests: The authors declare no conflict of interest

In this study, different planar inductor topologies were studied to evaluate their characteristic parameters' variation range upon approaching Fe- and Cu-based shield plates. The use of such materials can differently alter the electrical properties of planar inductors such as the inductance, resonant frequency, resistance, and quality factor, which could be useful in multiple devices, particularly in inductive sensing and radio-frequency (or RF) applications. To reach an optimal design, five different square topologies, including spiral, tapered, non-spiral, meander, and fractal, were built on a printed circuit board (PCB) and assessed experimentally. At the working frequency of 1 MHz, the results showed a decrease in the inductance value when approaching a Cu-based plate and an increase with Fe-based plates. The higher variation range was noticeable for double-layer topologies, which was about 60% with the Cu-based plate. Beyond an intrinsic deflection frequency, the inductance value began to decrease when approaching the ferromagnetic plate because of the ferromagnetic resonance (FMR). It has been shown that the FMR frequency depends on the inductor topology and is larger for the double-layer spiral one. The Q -factor was decreasing for all topologies but was much faster when using ferromagnetic plates because of the FMR, which intensely increases the track resistance. The resonant frequency was increasing for all double-layer topologies and decreasing for single-layer ones, which was mainly due to the percentage change in the stray capacitance compared to the inductance variation. The concept of varying inductors by metal shielding plates has great potential in a wide range of nondestructive sensing and RF applications.

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., Competing Interests: Conflict of interestThe authors announce that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© Indian Association for the Cultivation of Science 2022.)

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., Competing Interests: Conflict of interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2022.)

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 (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%)., (© The Author(s), under exclusive licence to Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2022, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

In this paper, a pioneer partial discharge (PD) loop antenna sensor is presented and examined. It is made of a 70-turn square planar inductor with a side length of 1.8 mm, which is fabricated on top of a silicon substrate in complementary metal oxide semiconductor technology. The microsensor ability to detect corona PD is demonstrated once connected in series with a 60 dB gain amplifier. The behavior is studied at different separation distances from the line through which the PD pulses flow. At 5 cm away, a damped sinusoidal induced voltage with an amplitude of about 100 mV has been measured. The output signal spectrum is highly concentrated around a central resonance frequency of ∼5 MHz. The microsensor response is compared with those of other industrial sensors from Techimp, i.e., horn antennas and high-frequency current transformer sensors. The presented on-chip sensor can be considered a non-intrusive competing solution compared with other heavy and expensive commercial sensors due to its lightweight, compact size, and low cost. In addition, it shows an acceptable signal to noise ratio compared with other commercial electromagnetic wave-based sensors.

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., Competing Interests: Conflict of interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021.)

The location of the Pd atoms in Pd2Au36(SC2H4Ph)24, is studied both experimentally and theoretically. X-ray photoelectron spectroscopy (XPS) indicates oxidized Pd atoms. Palladium K-edge extended X-ray absorption fine-structure (EXAFS) data clearly show Pd-S bonds, which is supported by far infrared spectroscopy and by comparing theoretical EXAFS spectra in R space and circular dichroism spectra of the staple, surface and core doped structures with experimental spectra.