Analysis of the impact of metal thickness and geometric parameters on the quality factor-Q in integrated spiral inductors by means of artificial bee colony technique

The goal of this present paper is to design, analysis the influence of the inductor geometrical parameters and the effect of the metal thickness on the quality factor-Q in integrated square spiral inductor using an efficient application of the artificial bee colony (ABC) algorithm. The inductors were optimized at 2.4 GHz to determinate their major geometrical dimensions (sp, w, din…) and their number of turns, for uses in radio-frequency integrated circuits (RFICs). The optimization results are validated by the simulation using an electromagnetic simulator (ADS-Momentum). Using matlab software, the study on the impact of the effect of geometrical parameters and the effect of metal thickness, on the factor of quality-Q of spiral inductors, is shown. We first reported that it is possible to improve Q-factors further by increasing the metal thickness, and in the design of inductor; a compromise must be reached between the value of w, n, sp and din to achieve the desired quality factor-Q and other electrical parameters

Optimal interdigitated electrode sensor design for biosensors using multi-objective particle-swarm optimization

Interdigitated electrodes (IDEs) are commonly employed in biological cellular characterization techniques such as electrical cell-substrate impedance sensing (ECIS). Because of its simple production technique and low cost, interdigitated electrode sensor design is critical for practical impedance spectroscopy in the medical and pharmaceutical domains. The equivalent circuit of an IDE was modeled in this paper, it consisted of three primary components: double layer capacitance, Cdl, solution capacitance, CSol, and solution resistance, RSol. One of the challenging optimization challenges is the geometric optimization of the interdigital electrode structure of a sensor. We employ metaheuristic techniques to identify the best answer to problems of this kind. multi-objective optimization of the IDE using multi-objective particle swarm optimization (MOPSO) was achieved to maximize the sensitivity of the electrode and minimize the Cut-off frequency. The optimal geometrical parameters determined during optimization are used to build the electrical equivalent circuit. The amplitude and phase of the impedance versus frequency analysis were calculated using EC-LAB® software, and the corresponding conductivity was determined

Unloaded quality factor optimization of substrate integrated waveguide resonator using genetic algorithm

The main objective purpose of this paper is to study the enhancement techniques of the unloaded quality factor of substrate integrated waveguide (SIW) resonator, given that the quality of filters depends first on the quality of the resonators that compose it. Performance enhancement is achieved by employing a MATLAB-based genetic algorithm to optimize the geometrical parameters of the SIW resonator by iterative convergence to the target frequency (10 GHz frequency). On the other hand, the Ansys HFSS tool is used to model and optimize the SIW resonator with the suitable transition and plot the S-parameters for a frequency sweep range to validate its property. The results obtained allow increasing the unloaded Q-factor to be more than 1609 and reducing not only insertion and return losses but also reducing the size of the resonator. The proposed SIW resonator with its small size and low loss is directly useful for microwave and millimeter-wave applications

Bio-inspired intelligence for minimizing losses in substrate integrated waveguide

This paper presents a study of various types of losses in substrate-integrated waveguides (SIW) using a genetic algorithm. Three main types of losses are considered and examined separately: conductor loss, dielectric loss, and radiation loss. Furthermore, the current analysis allows for a physical understanding of the loss impacts as well as the creation of design guidelines to reduce losses at 10 GHz frequency while keeping the miniaturized size of the SIW. Validation results obtained using the software Ansys HFSS, verify that the attenuation constant of the SIW can be significantly reduced to  0.4 dB/m, the Insertion loss S21 to -0.2 dB and the return loss to -38 dB if the geometric parameters are chosen properly. This study enables us to identify the source of losses in a SIW and, as a result, eliminate any type of dispersion. That demonstrates the usability of SIW technologies in the design of microwave circuits used in Internet of things applications

Design and miniaturization of a microsystem to power biomedical implants using grey wolf optimizer-based cuckoo search algorithm

One of the greatest techniques, inductive coupling is frequently utilized in the biomedical sector for wireless energy transfer to implants. The aim of this article is to develop and analyze the effect of inductor geometrical characteristics, distance between transmitter (TX) and receiver (RX) and also the operating frequency on the wireless power transfer system, using grey wolf optimizer-based cuckoo search (GWO-CS) algorithm. Power transfer efficiency (PTE), power provided to load, and other critical components must all be improved or maximized and miniaturaze the microsystem proposed. The invention, design, and optimization of coils square spirals in a wireless energy transfer system using a resonant inductive link are the emphasis of this paper. The GWO-CS approach is evaluated to existing methods, demonstrated by simulations and to demonstrate the effectiveness of the suggested strategy

An enhanced EEG prediction system for motor cortex-imagery tasks using SVM

After the emergence of many new technologies, it is possible to search on the development of new devices that can be predicting what is happening in human thought based on EEG signals, such as the method used this paper contains a novel classification of the EEG signals acquired for multiple motor cortex-imagery tasks, where this method was based on the use of the Extra Tree algorithm to well select the best channels that were used for the acquisition of EEG signals, then the use of support vector machine (SVM) algorithm for data classification, moreover this work uses grey wolf optimizer (GWO) algorithm to improve all SVM parameters quickly and to converge the accuracy of the system towards the highest possible values. As a result, this work shows that the accuracy of prediction of motor cortex-imagery based EEG signals can be increased more than 99%. Also, this paper contains a comparison with other methods of the literature

Optimal Interdigitated Electrode Sensor Design for biosensors using Differential Evolution Algorithm

Optimization of interdigitated electrode sensor design is essential for practical impedance spectroscopy in the medical and pharmaceutical fields because of their easy fabrication procedure and inexpensive. The geometry presents a prospective for ameliorating sensitivity over other microelectrode designs. The geometric optimization of a sensor’s structure with interdigital electrodes is one of the difficult optimization problems. To solve this type of problem, we use metaheuristic methods to find the optimal solution. The method chosen in this paper is the differential evolution algorithm DE, which is widely used to solve the overall optimization problem. We will optimize the geometrical parameters of the interdigitated electrodes by minimizing the FLow, the proper band [FLowFHigh] using MATLAB script, the validity of the obtained results is investigated using ADS tool

Optimal design of inductive coupled coils for biomedical implants using metaheuristic techniques

Powering implanted biomedical devices (IMDs) and sensors is a major obstacle for researchers in the microelectronics field. Such as the problem of miniaturization, increasing the distance between the external part (TX) and the internal part (RX), and the improvement of the power transfer efficiency (PTE), … The purpose of this article is to compare two strategies for optimizing component characteristics for a wireless energy transfer system (coupling of two coils), based on the new Figure-of-Merit (FoM) or iterative procedure (IP), and genetic algorithm (GA), in order to have a power transfer efficiency equal to 15% and 94.18 % respectively for a separation distance d = 12cm