Array Design Research Articles

Dual magnetoelectric antenna array with enhanced bandwidth and sensitivity for low-frequency communications

The magnetoelectric coupling effect demonstrated immense potential for miniaturizing antenna applications. However, due to the resonant nature of magnetoelectric (ME) antennas, their bandwidth tended to be relatively narrow. To address this limitation, our study introduced an array design based on coupled ME antennas. A tri-layer FeGa–PZT8–FeGa laminate structure was employed to construct the ME antennas, which utilized inter-array coupling to broaden the frequency range. Both the central frequency and sensitivity of the array structure were theoretically analyzed, and two methods for extending the frequency were proposed. By coupling two ME antennas of similar frequency in the series mode, the arrayed ME antennas exhibited enhanced sensitivity, increasing from 0.225 and 0.247 to 0.413 mV/nT, and an expanded bandwidth from 0.92–1.03 to 1.4 kHz, indicating improved performance through combined configuration. On the other hand, by coupling two ME antennas of different frequencies together in the series mode, a dual-frequency (97.8/98.97 kHz) ME antenna array was formed. The communication capabilities of the ME antenna array under weak magnetic fields were demonstrated using amplitude shift keying and frequency shift keying modulation methods. The designed array of ME antennas elevated low-frequency communication performance and possessed excellent magnetic field detection capabilities, thereby offering a cost-effective technological pathway for bioelectronic and marine communication design.

Design of a square-horn hybrid plasmonic nano-antenna array using a flat lens for optical wireless applications with beam-steering capabilities

This paper introduces a Hybrid Plasmonic Nano-Antenna (HPNA) with a gradient-index dielectric flat lens modeled with different materials to enhance and steer the radiation in a particular direction based on a phase shift array. Firstly, the design of hybrid plasmonic Nano-Antenna (NA) is introduced and analyzed considering different horn-shapes such as diamond, hexagonal, circular, rectangular, and square shapes. The commercial software Computer Simulation Technology-Microwave Studio (CST-MWS) is used to analyze the radiation characteristics of the plasmonic NAs at the standard telecommunication wavelength of 1,550 nm. The produced horn-shaped nano-antenna made up from gold cladding with low- and high-index dielectric materials of SiO2 and InGaAs, respectively. The gain of the Square Horn shape Hybrid Plasmonic Nano-Antenna (SHHPNA) achieves the greatest gain with a value of 10.7 dBi at the desired frequency and the return loss reached -18.09 dB due to the wide aperture area for SHHPNA, which results in a narrower beam-width and higher gain. Moreover, by using two different shapes of dielectric flat lens to enhance the antenna’s performance by improving directivity while correspondingly reducing beam-width, the gain is enhanced and reaches 16.7 for SHHPNA with a circular lens and 16.9 for SHHPNA with a rectangular lens compared with the traditional NA that equal to 9.03 dBi. The main lobe for SHHPNA with each lens is more directed, with Side Lobe Level (SLL) and Half Power Beam-Width (HPBW) of -13.1 dB and 16.5° for SHHPNA with a circular lens and -15.1 dB and 15.4° for SHHPNA with a rectangular lens, respectively. In addition, the array configuration was investigated, and the gain was found to be 21 dBi for the single row array of 4×1 and 23.2 dB for the array of 3×3. Moreover, the array of 4×1 and 3×3 with +90° showed gains of 18.6 dBi and 20.7 dBi, respectively, compared to traditional paper with gains of 11.20 dBi and 13.1 dBi.

Design and Performance Analysis of Dielectric Resonator Antenna Array for 5G mm-Wave Ground-Based Navigation and Wireless Applications

Design and Performance Analysis of Dielectric Resonator Antenna Array for 5G mm-Wave Ground-Based Navigation and Wireless Applications

Alphabet Handwriting Recognition: From Wood-Framed Hydrogel Arrays Design to Machine Learning Decoding.

Handwriting recognition is a highly integrated system, demanding hardware to collect handwriting signals and software to deal with input data. Nonetheless, the design of such a system from scratch with sustainable materials and an easily accessible computing network presents significant challenges. In pursuit of this goal, a flexible, and electrically conductive wood-derived hydrogel array is developed as a handwriting input panel, enabling recognizing alphabet handwriting assisted by machine learning technique. For this, lignin extraction-refill, polypyrrole coating, and polyacrylic acid filling, endowing flexibility, and electrical conduction to wood are sequentially implemented. Subsequently, these woods are manufactured into a 5×5 array, creating a matrix of signals upon handwriting. Efficient handwritten recognition is then achieved through appropriate manual feature extraction and algorithms with low complexity within a computing network, as demonstrated in this work, the strategic choice of expertise-based feature engineering and simplified algorithms effectively boost the overall model performance on handwriting recognition. With potential adaptability, further applications in customized wearable devices and hands-on healthcare appliances are envisioned.

Study on a novel dual-row vertical axis wind turbine with J-Shaped blades by using numerical methods and optimization

ABSTRACT This study investigates the benefits of using J-shaped blades in a dual-row Darrieus wind turbine (DDWT), combining two innovative ideas whose simultaneous impact on the self-starting capability of Darrieus turbines has not been explored. The performance of the turbine was simulated using Computational Fluid Dynamics (CFD) and optimized using both the Taguchi method and a combined Machine Learning and Genetic Algorithm (ML-GA) technique. Three main operating parameters, including the tip speed ratio (λ), radial ratio (δ), and angular distance (ϕ) of dual-row turbines, were investigated across four levels using an L25 orthogonal array design. According to the Taguchi analysis, the impact of the parameters on the power output was ranked in the order of λ > δ > ϕ. After comparison, the optimized turbine predicted by the ML-GA technique was chosen due to the superior accuracy of the ML-GA approach compared to the Taguchi method. The optimal configuration of a DDWT with J-shaped blades was predicted at λ = 2.15, δ = 1.39, and ϕ = 75.36, with a Cp of 0.49 based on CFD simulations. Compared to the single-row wind turbine, the proposed turbine showed a significant increase of the Cp at low tip speed ratios resulting in a better self-starting performance.

IEA Wind Task 49: Reference Site Conditions for Floating Wind Arrays

Abstract The commercial-scale deployment of floating offshore wind (FOW) projects is expected to take place in a diverse range of sites that may differ significantly from existing fixed-bottom projects. FOW farms are particularly sensitive to the water depth and the meteorological and oceanographic (metocean) and geotechnical conditions at the project site due to the wave-induced system motions and loads as well as the anchoring system constraints imposed by the seafloor conditions. Uncertainty around the site conditions will permeate through all aspects of project design, leading to suboptimal and overly conservative designs, increased costs, and adversely affected performance. As FOW expands into a global industry, metocean and geotechnical conditions will increasingly vary for projects located in different geographic regions or in far-from-shore, deep-water sites. This study represents the outputs of work package 1 of International Energy Agency Wind Task 49, which focuses on the integrated design of floating wind arrays. The primary goal of this study is to establish the type of parameters and constraints required to characterize FOW array reference sites; provide a realistic and publicly available set of reference site conditions to the FOW community as a baseline set of data for individual research projects; identify and categorize any critical gaps in the existing data or methodologies required to define reference site characteristics; and inform and support the design of reference FOW arrays. A building block concept was developed for synthesizing reference sites for the design of FOW arrays. The building blocks include three classes of site conditions focusing on the techno-economic design of FOW projects: metocean conditions, seabed conditions, and coastal infrastructure. All reference site data produced and collected in this study are publicly available.

Highly Sensitive Phased Array Probes based on Capacitive Micromachined Ultrasonic Transducers

Capacitive Micromachined Ultrasonic Transducers (CMUTs) offer a wide freedom of design for ultrasonic phased arrays. They are characterized, in comparison to piezoelectric transducers, by a higher sensitivity in receiving and a wider bandwidth based on their physical properties. Especially in combination with integrated preamplifiers the high receiving sensitivity compensates or rather overcompensates the lower transmission power of the CMUT in single probe applications with pulse-echo technique. This asymmetric behavior opens new opportunities in the application. In medical diagnostics it allows to meet the maximum permissible ultrasonic radiation force with the best sensitivity. In nondestructive testing the transmission power can be increased by the combination of a piezoelectric probe for transmitting and a CMUT probe for receiving. Especially in double probe techniques, such as pitch-catch or time-of-flight diffraction (TOFD), this is an efficient extension of the conventional approach with two piezoelectric transducers. The CMUT array probes developed by Fraunhofer IPMS with integrated preamplifier and bias voltage converter powered by a standard USB-A connector can be applied as one to one substitute for piezoelectric phased arrays with commercially available ultrasonic devices without adaption or additional electronics. The CMUT arrays are best suited for immersion technique and medical sonography because of their natural matching to water-like materials. They are applicable as well for solid surfaces with a special coating. We present the first results of ultrasonic imaging with our CMUT array probes in comparison with a commercially available piezoelectric phased array probe.

Performance of synthetic DAS as a function of array geometry

Distributed Acoustic Sensing (DAS) can record acoustic wavefields at high sampling rates and with dense spatial resolution difficult to achieve with seismometers. Using optical scattering induced by cable deformation, DAS can record strain fields with ones of meters spatial resolution. However, many experiments utilizing DAS have relied on unused, dark telecommunication fibers. As a result, the geophysical community has not fully explored DAS survey parameters to characterize the ideal array design. This limits our understanding of guiding principles in array design to deploy DAS effectively and efficiently in the field. A better quantitative understanding of DAS array behavior can help improve the quality of the data recorded by guiding the DAS array design. Here we use array response functions as well as beamforming and back-projection results from forward modelling calculations to assess the performance of varying DAS array geometries to record regional and local sources. A regular heptagon DAS array demonstrated improved capabilities for recording regional sources over segmented linear arrays, with potential improvements in recording and locating local sources. These results reveal DAS array performance as a function of geometry and can guide future DAS deployments.

Multichannel Sensor Array Design for Minimizing Detector Complexity and Power Consumption in Ionoacoustic Proton Beam Tomography

Ionoacoustic tomography exploits the acoustic signal generated by the fast energy deposition along the path of pulsed particle beams to reconstruct with sub-mm precision the dose deposition, with promising envisioned applications in hadron therapy treatment monitoring. State-of-the-art ionoacoustic detectors mainly rely on single-channel sensors and time-of-flight measurements to provide 1D localization of the maximum dose deposition at the so-called Bragg peak. This work investigates the design challenges of multichannel sensors for ionoacoustic tomography in terms of their ability to accurately reconstruct the dose deposition of a 200 MeV clinical proton beam, highlighting the impact of the number of channels in the array and their directivity. A complete acoustic model of the sensors and environment has been developed and used to find an optimum tradeoff between accuracy, evaluated numerically through the gamma index, and hardware complexity due to higher channel numbers, thus minimizing the system-level power consumption of the detector.

Optimization of aloe vera‐sodium alginate composite coating using L16 orthogonal design for extension of shelf life of mushroom

AbstractWhite button mushrooms are highly nutritive, rich in various macro and micro nutrients, however, have a short shelf life with weight loss (WL), enzymatic browning, and loss in firmness as the major quality defects. The present study was carried out to investigate the effect of aloe vera‐sodium alginate (AV‐SA) composite coating on the quality attributes of mushroom. The development of coating formulations containing 2% sodium alginate along with varying concentration of aloe vera gel 20%–80% and storage time 4–16 days was planned using a 2‐factor 4‐level orthogonal array (L16) design of Taguchi technique. The influence of both the process parameters on the WL, total soluble solids (TSS), respiration rate (RR), browning index (BI), firmness, electrolyte leakage rate (EL), malondialdehyde (MDA), ascorbic acid (AA), total phenolic content (TPC), enzymes activity (polyphenol oxidase and peroxidase), and yeast and mold count (YMC) were evaluated and the optimized level of parameters was determined on the basis of the highest S/N ratios of the responses. The results indicated that 60% AV‐SA composite coating could extend the shelf life of white button mushrooms for up to 8 days with retarded loss in weight, firmness, AA, and TPC and reduced increase in TSS, BI, EL, MDA with controlled enzymatic activity, RR, and YMC.

Retraction Note: Design of linear array for shaped beams using enhanced flower pollination optimization algorithm

Retraction Note: Design of linear array for shaped beams using enhanced flower pollination optimization algorithm

Multi-Objective Design and Optimization of Hardware-Friendly Grid-Based Sparse MIMO Arrays

A comprehensive design framework is proposed for optimizing sparse MIMO (multiple-input, multiple-output) arrays to enhance multi-target detection. The framework emphasizes efficient utilization of antenna resources, including strategies for minimizing inter-element mutual coupling and exploring alternative grid-based sparse array (GBSA) configurations by efficiently separating interacting elements. Alternative strategies are explored to enhance angular beamforming metrics, including beamwidth (BW), peak-to-sidelobe ratio (PSLR), and grating lobe limited field of view. Additionally, a set of performance metrics is introduced to evaluate virtual aperture effectiveness and beamwidth loss factors. The framework explores optimization strategies for the partial sharing of antenna elements, specifically tailored for multi-mode radar applications, utilizing the desirability function to enhance performance across various operational modes. A novel machine learning initialization approach is introduced for rapid convergence. Key observations include the potential for peak-to-sidelobe ratio (PSLR) reduction in dense arrays and insights into GBSA feasibility and performance compared to uniform arrays. The study validates the efficacy of the proposed framework through simulated and measured results. The study emphasizes the importance of effective sparse array processing in multi-target scenarios and highlights the advantages of the proposed design framework. The proposed design framework for grid-spaced sparse arrays stands out for its superior efficiency and applicability in processing hardware compared to both uniform and non-uniform arrays.

Advancing equine genomics: the development of a high density Axiom_Ashwa SNP chip for Indian horses and ponies.

The unique horse and pony breeds of India are declining at an alarming rate. These horses have been integral to the Indian culture and customs for centuries and represent a valuable genetic resource. It is imperative to harness the potential of this equine genetic resource that urgently needs conservation. The study highlights the design and development of a high density SNP array, the Axiom_Ashwa to aid in the genetic analysis and conservation efforts for Indian horse and pony breeds. With 613,950 SNPs, this chip offers extensive genome coverage having an average inter-marker distance of 4kb. The Axiom_Ashwa has been validated on a larger set of diverse indigenous samples as well as Thoroughbreds, demonstrating a high call rate of 99.4% and robustness for genotyping indigenous breeds. Linkage disequilibrium (LD) analysis showed higher average LD in Indian breeds compared to exotic breeds, suggesting a limited effective population size and recent bottlenecks. Phylogenetic and population stratification analyses using PCA and DAPC clearly distinguished horses, ponies and Thoroughbreds, confirming the efficacy of the Axiom_Ashwa chip. These findings underscore the urgent need for conservation efforts for Indian horse breeds, which have experienced significant drop in population size. The Axiom_Ashwa SNP chip offers advantages such as cost-effectiveness and high throughput, providing a more accurate genetic representation of Indian horses.

Ultrasonic-Assisted Extraction and Antioxidant Evaluation of Resveratrol from Peanut Sprouts

The orthogonal array design method was used to optimize ultrasonic-assisted extraction of resveratrol from peanut sprouts. The results showed that the highest extraction yield of resveratrol using ultrasonic-assisted extraction could be up to 1.1%. The optimal extraction conditions were liquid to solid ratio of 30:1 (mL/g) and ethanol concentration of 80% (v/v) as solvent for 40 min at the temperature of 70 °C. AB-8 macroporous adsorption resin was used to purify the crude extract and the resveratrol content increased to 47.5% after one treatment run. The optimal adsorption parameters were initial concentrations in the sample solution of 2 mg/mL, a pH of 5.0, a flow rate of 2 mL/min, and a temperature of 25 °C. The optimal desorption parameters were 60% ethanol and a flow rate of 1 mL/min. The chemical composition of the peanut sprout’s resveratrol sample was investigated via HPLC, and the predominant constituents were found to be protocatechuic acid, catechins, caffeic acid, epicatechuic acid, resveratrol, and rutin. The antioxidant activities of the resveratrol were measured via the following different analytical methods: reducing power, 2,2-diphenyl-1-picrylhdrazyl (DPPH), hydroxyl radical-scavenger activity, superoxide radical-scavenger activity, the β-carotene bleaching test, and the scavenging nitrite test. The results indicated that the resveratrol in peanut sprouts have significant antioxidant activities and can be used as a source of potential antioxidant. And peanut sprout’s resveratrol has the potential and valuable application to be used as a new type of resveratrol resource. The finding of this study can provide some theoretical reference for the comprehensive utilization of peanut resources in the development of antioxidant health foods.

Marine predator’s algorithm-based linear and elliptical antenna array design for 5G communication

The highly efficient linear and elliptical antenna array design presented in this article is intended to synthesize far-field radiation patterns for 5G communication. The objective is to achieve the best possible radiation pattern, which includes a lower side lobe level (SLL) and a narrower half-power beam width (HPBW). A low SLL is crucial to minimize intervention in the entire side lobe region, whereas long-distance communication requires a low HPBW. The marine predator’s algorithm (MPA) is used here to determine the optimal feeding currents to each array element to reduce the SLL and HPBW values. Two linear antenna array (LAA) design examples and the three elliptical antenna array (EAA) design examples are discussed in this article which are achieved using the optimal current excitations to each array element. Two well-established evolutionary optimization techniques, namely the genetic algorithm (GA) and the differential evolution (DE) technique, are also employed for comparison to demonstrate the superiority of the MPA optimization-based technique. The results achieved utilizing the MPA show the improvement of SLL contraction compared to the uniform antenna array and the methods affirmed in the recently published article.

The acoustic Galton board

Phononic crystals are a class of materials with periodic structures that influence the propagation characteristics of acoustic waves through periodically arranged structural units. Here, we have developed the acoustic Galton board (AGB), a groundbreaking apparatus that serves as a cost-effective and user-friendly tool for demonstrating phononic crystal properties such as band gaps, Bragg scattering, and local resonance. The device comprises an elastic wave signal generator, an enhanced Galton board featuring a sophisticated pillar-nail array, and a signal receiver. The experimental results we have obtained demonstrate the significant impact of the AGB on elastic wave dispersion, effectively creating bandgaps that impede wave transmission within specific frequency ranges while allowing unhindered propagation in others. Furthermore, the AGB can simulate phononic crystals using both the Bragg scattering mechanism, achieved through the design of periodic rigid pillar-nail arrays, and the locally resonant mechanism, facilitated by the design of pillar-nail arrays with composite material structures. Additionally, the AGB can extend its applications to serve as a simulation tool for elastic metamaterials.

A certain examination on heterogeneous systolic array (HSA) design for deep learning accelerations with low power computations

Acceleration techniques play a crucial role in enhancing the performance of modern high-speed computations, especially in Deep Learning (DL) applications where the speed is of utmost importance. One essential component in this context is the Systolic Array (SA), which effectively handles computational tasks and data processing in a rhythmic manner. Google's Tensor Processing Unit (TPU) leverages the power of SA for neural networks. The core SA's functionality and performance lies in the Computation Element (CE), which facilitates parallel data flow. In our article, we introduce a novel approach called Proposed Systolic Array (PSA), which is implemented on the CE and further enhanced with a modified Hybrid Kogge Stone adder (MHA). This design incorporates principles to expedite computations by rounding and extracting data model in SA as PSA-MHA. The PSA, utilizing a data flow model with MHA, significantly accelerates data shifts and control passes in execution cycles. We validated our approach through simulations on the Cadence Virtuoso platform using 65 nm process technology, comparing it to the General Matrix Multiplication (GMMN) benchmark. The results showed remarkable improvements in the CE, with a 30.29 % reduction in delay, a 23.07 % reduction in area, and an 11.87 % reduction in power consumption. The PSA outperformed these improvements, achieving a 46.38 % reduction in delay, a 7.58 % reduction in area, and an impressive 48.23 % decrease in Area Delay Product (ADP). To further substantiate our findings, we applied the PSA-based approach to pre-trained hybrid Convolutional and Recurrent (CNN-RNN) neural models. The PSA-based hybrid model incorporates 189 million Multiply-Accumulate (MAC) units, resulting in a weighted mean architecture value of 784.80 for the RNN component. We also explored variations in bit width, which led to delay reductions ranging from 20.17 % to 30.29 %, area variations between 13.08 % and 32.16 %, and power consumption changes spanning from 11.88 % to 20.42 %.

Research on the fusion imaging method of sign coherence and time reversal for Lamb wave sparse array

Time-reversal imaging struggles to detect plate-like structures due to interference from Lamb wave mode conversion and the processing demands, leading to less effective outcomes. This paper proposes a sign coherence factor and time reversal fusion (SCF-TR) imaging method based on amplitude and phase estimation. This method removes the coherence of array signals during signal reversal and refocusing. It reintroduces the sign coherence component to reduce interference from non-target scattered waves and partially overcome the constraints imposed by the Rayleigh criterion. The method allows imaging at a resolution smaller than the wavelength of Lamb and enhances the quality of the resulting images. In addition, a sparse array design utilizing the White Shark Optimisation Algorithm (WSO) is proposed to streamline the SCF-TR calculation process. This design utilizes sparse full matrix data to improve imaging efficiency. The experimental results show that for single blind hole defects, the SCF-TR method improves the array performance metrics and signal-to-noise ratio by 22.46% and 42.50%, respectively, compared to the TR method. For multiple asymmetric blind hole defects, when the defect size exceeds the resolution threshold, SCF-TR accurately reflects the position and morphology of defects smaller than the wavelength. When the defect size is below the resolution threshold, SCF-TR achieves super-resolution imaging. The sparse array designed using the White Shark Optimization algorithm demonstrates good sidelobe characteristics, effectively reducing sidelobe noise without reducing the array aperture. Moreover, the SCF-TR imaging time is reduced by approximately half while maintaining imaging accuracy.

A novel circularly polarized antenna array methodology for early identification of kidney tumors

Kidney cancer is a significant health concern worldwide, with early detection crucial for successful treatment outcomes. Recently, there has been an increasing focus on investigating affordable and non-intrusive methods for detecting cancer at its early stages. This proposed approach delves into the utilization of antenna arrays to identify kidney cancer. Specifically, antenna array with circular polarization has been crafted to identify tumors in the human kidney. This array design has been implemented using CST software, operating at 2.4 GHz. The antenna array having a dimension of 150 mm x 150 mm. The array consists of four-square patches each having a length of 30 mm and the spacing between the patches is preferred to be 20 mm for ensuring the mutual coupling. FR4 substrate is used with the relative permittivity 4.3 and 1.6 mm thickness. The axial ratio of the circularly polarized antenna is 0.9 dB at 2.4 GHz. The reflection coefficient S 11 = –30dB. The renal phantom in humans has been built with the kidney, adrenal gland, ureter, skin, fat, and muscle components to allow for precise simulation. Following that, four stages of cancer tumors were built employing all of the necessary qualities. For every stage of the cancer tumor, the reflection coefficient growth and resonance frequency shift are calculated. For the initial stages, the resonance frequency shift is very low. Consequently, the primary determinant of detection is the rise in S 11 . For 3rd and 4th stages of the tumor, there is a significant change in resonance frequency and increase S 11 , which facilitates identification. The calculated specific absorption rate (SAR) is a smaller amount than the safety thresholds, indicating that using this method is safe. Overall, this research points to a novel, easy-to-use method for kidney cancer screening. This method has the following benefits: it is non-invasive, safe, quick, affordable, and comfortable, and it emits no ionizing radiation during the measurement process. Furthermore, a range of output parameters such as gain, directivity, and polar radiation have been accurately computed.

Arrayed multi-layer piezoelectric sensor based on electrospun P(VDF-TrFE)/ZnO with enhanced piezoelectricity

Flexible pressure sensors can maintain good pressure sensing capabilities even under arbitrary degrees of deformation, which are widely used in fields such as robotic perception, physiological signal detection and wearable electronics. Currently, piezoelectric-based flexible pressure sensors face significant limitations in terms of large-area, high-sensitivity, and high-resolution pressure detection. Targeted research efforts primarily focus on enhancing the performance of piezoelectric sensors by optimizing the properties of the sensitive layer piezoelectric material and modulating device structural design. This study introduces a novel multilayer array design for flexible composite piezoelectric sensors. A high-voltage electrospinning selective deposition process is proposed to fabricate arrayed nanofiber mats. Patterned electrospun films can be automatically patterned by patterned AgNW electrodes, which allows manual alignment of patterns for subsequent stacking. Compared to sensor based on P(VDF-TrFE) prepared under the same conditions, the sensitivity of the multi-layer P(VDF-TrFE)/ZnO sensor increased from 2.82 mV/kPa to 8.30 mV/kPa, providing an effective approach for highly sensitivity wearable devices with short response time (∼5 ms).