Compact Size Research Articles

Rapid in-situ calibration of computational micro-spectrometer with few-shot meta-learning

Computational micro-spectrometers comprised of detector arrays and encoding structure arrays, such as on-chip Fabry-Perot (FP) cavity filters, have great potential in many in-situ applications owing to their compact size and snapshot imaging ability. Given manufacturing deviation and environmental influence are inevitable, easy and effective calibration for spectrometer is necessary, especially for in-situ applications. Currently calibration strategies based on iterative algorithms or neural networks require accurate measurements of pixel-level (spectral) encoding functions through monochromator or large amounts of standard samples. These procedures are time-consuming and expensive, thereby impeding in-situ applications. Meta-learning algorithms with few-shot learning ability can address this challenge by incorporating the prior knowledge in the simulated dataset. In this work, we propose a meta-learning algorithm free of measuring encoding function or large amounts of standard samples to calibrate a micro-spectrometer with manufacturing deviation effectively. Our micro-spectrometer comprises 16 types of FP filters covering a wavelength range of 550-720 nm. The center wavelength of each filter type deviates from the design up to 6 nm. After calibration with 15 different color data, the average reconstruction error on the test dataset decreased from 7.2 × 10 − 3 to 1.2 × 10 − 3, and further decreased to 9.4 × 10 − 4 when the calibration data increased to 24. The performance is comparable to algorithms trained with measured encoding function both in reconstruction error and generalization ability. We estimated that the cost of in-situ calibration through reflectance measurements of color chart decreased to one percent of the cost through monochromator measurements. By exploiting prior deviation information in simulation data with meta-learning, the efficiency and cost of calibration are significantly improved, thereby facilitating the large-scale production and in-situ application of micro-spectrometers.

Advancing Cycling Safety: On-Bike Alert System Utilizing Multi-Layer Radar Point Cloud Clustering for Coarse Object Classification

Cyclists are considered to be vulnerable road users (VRUs) and need protection from potential collisions with cars and other vehicles induced by unsafe driving, dangerous road conditions, or weak cycling infrastructure. Integrating mmWave radars into cycling safety measures presents an efficient solution to this problem given their compact size, low power consumption, and low cost compared to other sensors. This paper introduces an mmWave radar-based bike safety system designed to offer real-time alerts to cyclists. The system consists of a low-power radar sensor affixed to the bicycle, connected to a micro-controller, and delivering a preliminary classification of detected obstacles. An efficient two-level clustering based on the accumulation of radar point clouds from multiple frames with a temporal projection from previous frames into the current frame is proposed. The clustering is followed by a coarse classification algorithm in which we use relevant features extracted from the resulting clusters. An annotated RadBike dataset composed of radar point cloud data synchronized with RGB camera images is developed to evaluate our system. The two-level clustering outperforms the DBSCAN algorithm, achieving a v-measure score of 0.91, compared to 0.88 with classical DBSCAN. Different classifiers, including decision trees, random forests, support vector machines (SVMs), and AdaBoost, have been assessed, with an overall accuracy of 87% for the three main object classes: four-wheeled, two-wheeled, and others. The system has the ability to improve rider safety on the road and substantially reduce the frequency of incidents involving cyclists.

A High-Gain Metallic-Via-Loaded Antipodal Vivaldi Antenna for Millimeter-Wave Application

This paper presents a miniaturized-structure high-gain antipodal Vivaldi antenna (AVA) operating in the millimeter-wave (mm-wave) band. A gradient-length microstrip-patch-based director is utilized on the flares of the AVA to enhance gain. Additionally, an array of metallic vias is incorporated along the lateral and horizontal edges of the antenna for further gain enhancement and bandwidth extension. Based on the proposed structure, the AVA can achieve a peak gain of 11.9 dBi over a relative bandwidth of 71.24% within 16.5–36.6 GHz as measured, while the electrical dimension is only 1.54 × 2.69 × 0.07 λc3. The measured results show good agreement with the simulated ones. Owning the characteristics of being high-gain and ultra-wideband, and having a compact size, the proposed AVA can be a competitive candidate for future millimeter-wave communication.

High-speed tooth-coil permanent magnet synchronous machine for motorized spindle application

The slender shape of the driving machine leads to a low rigidity and large axial thermal elongation of the motorized spindle, which deteriorates the machining precision. To solve these problems and pursue a more compact size, this paper investigates the feasibility of using a tooth-coil permanent magnet synchronous machine in a high-speed spindle, replacing the original motor that has the conventional distributed winding. Comprehensive performance and behavior of machines with distributed and tooth-coil windings are comparatively analyzed, in terms of the essential torque ripples, winding inductances, electromagnetic losses, rotor integrity, and heat dissipation of the spindle. Thorough numerical simulation results indicate that the newly designed tooth-coil winding solution shows significant advantages over the original design, regarding high rotor rigidity, low torque ripples, reduced electromagnetic losses, and reduced shaft thermal elongation. Prototypes and test setups for the high-speed tooth-coil machine are built, where preliminary measurements are carried out to validate the analysis results and system design.

Microstrip Quasi-Elliptic Absorptive Bandpass Filter with Ultra-Wide Reflectionless Range and Compact Size

Absorptive bandpass filters (ABPFs) are highly attractive in modern microwave communication systems due to their ability to internally absorb the harmful stopband RF-power reflections. This paper reports an approach to designing quasi-elliptic ABPFs with ultra-wide reflectionless range, enhanced selectivity, and compact size. The method is realized based on a fourth-order quasi-elliptic absorptive lowpass filter (ALPF) prototype with a simplified structure. This ALPF prototype exhibits both good impedance-matching over the whole normalized frequency domain and an adjustable transmission zero close to the passband. By applying an equivalent impedance transformer model, a coupled-line-based ABPF scheme is devised from the ALPF prototype, which eliminates conventional dispersive transmission line inverters, resulting in an ultra-wide reflectionless range and a compact size. Closed-form equations are derived to support the filter synthesis. A 2.45 GHz microstrip ABPF with 30% fractional bandwidth is designed for verification. The measured minimum in-band insertion loss is 0.83 dB and the reflectionless range of return loss better than 10 dB is from DC to 12.88 GHz. Both the upper and lower stopband suppression exceed 20 dB, with the upper stopband extending up to 6.80 GHz. The upper and lower out-of-band roll-off rates are 93.9 and 121.4 dB/GHz, respectively. The overall circuit size is 0.12 λg2.

Next generation single-domain antibodies against respiratory zoonotic RNA viruses

The global impact of zoonotic viral outbreaks underscores the pressing need for innovative antiviral strategies, particularly against respiratory zoonotic RNA viruses. These viruses possess a high potential to trigger future epidemics and pandemics due to their high mutation rate, broad host range and efficient spread through airborne transmission. Recent pandemics caused by coronaviruses and influenza A viruses underscore the importance of developing targeted antiviral strategies. Single-domain antibodies (sdAbs), originating from camelids, also known as nanobodies or VHHs (Variable Heavy domain of Heavy chain antibodies), have emerged as promising tools to combat current and impending zoonotic viral threats. Their unique structure, coupled with attributes like robustness, compact size, and cost-effectiveness, positions them as strong alternatives to traditional monoclonal antibodies. This review describes the pivotal role of sdAbs in combating respiratory zoonotic viruses, with a primary focus on enhancing sdAb antiviral potency through optimization techniques and diverse administration strategies. We discuss both the promises and challenges within this dynamically growing field.

Generation of optical vortex beams with bandwidth exceeding 550 nm using a helical fiber needle exhibiting strong mode coupling.

A strong-coupling helical fiber needle (HFN) is proposed and demonstrated for the realization of bandwidth-enhanced broadband optical vortex beam (OVB) generation. The HFN is based on a single mode fiber and operates at the dispersion-turning-point (DTP) of the lowest radial order of the cladding mode (i.e., LP11) but with a remarkably high mode coupling efficiency. By utilizing this novel, to the best of our knowledge, HFN, successful generation of the first-order OVB with an impressive bandwidth up to 556 nm at -10 dB and a center wavelength of ∼1570 nm has been achieved. This represents the broadest bandwidth demonstrated among all fiber grating-based OVB generators to date. The proposed HFN-based OVB generator exhibits a relatively compact size, ultra-wide bandwidth, and customizable center wavelength, making it highly promising for applications in optical vortex-based endoscopic imaging as well as particle detection and manipulation.

RBFNN-based UWB 4×4 MIMO Antenna Design with Compact Size, High Isolation, and Improved Diversity Performance for Millimeter-Wave 5G Applications

Abstract The millimeter-wave spectrum has emerged as a compelling solution to address the pressing need for high-datarate
capabilities in the development of 5G technology systems. Spanning between 20 GHz and 40 GHz, this spectrum
encompasses several prominent frequency bands crucial for advancing 5G applications. In light of this, our study
presents a thorough investigation into the design and performance of a compact cross-shaped slot broadband antenna,
complemented by a 4×4 Multiple-InputMultiple-Output (MIMO) configuration tailored for 5G operations at
28 GHz. The primary objective of this study is to develop an antenna system capable of achieving an extended bandwidth
ranging from 20 GHz to 40 GHz, effectively covering the crucial frequency bands essential for 5G millimeterwave(
mmWave) operations. To accomplish this, the optimization of antenna performance is meticulously carried out
using the Radial Basis FunctionNeuralNetworks (RBFNN) model. The RBFNNmodel serves as a robust tool for establishing
the intricate relationship between antenna dimensions, resonant frequency, and bandwidth. Subsequently,
the developed RBFNN model is employed to predict optimal antenna dimensions, ensuring resonance at 28 GHz and
meeting specified bandwidth targets. The single antenna is designed with a rectangular patch and a cross-shaped
slot and is constructed on the low loss Rogers RT Duroid 5880 substrate. This design reaches an outstanding bandwidth
of 19.5 GHz, and exhibits excellent radiation characteristics, with a high radiation efficiency of up to 99% and a
corresponding gain of 5.75 dB. The antenna’s design and performance are rigorously designed using HFSS software,
which is then compared to the results acquired using CST software. In addition, the proposed MIMO configuration
offers excellent performance in terms of key features such as small size (16 × 16.2 mm2), very wide bandwidth of 20
GHz, good gain of 6.75 high isolation exceeding 35 dB, and significant improvements in diversity performance measures
such as Envelope Correlation Coefficient (ECC), Diversity Gain (DG), Channel Capacity Loss (CCL), Total Active
Reflection Coefficient (TARC), and Mean Effective Gain (MEG). The potential of the proposed MIMO configuration
for high-speed applications is particularly remarkable. Practical verification of the MIMO configuration is carefully
carried out by fabrication andmeasurement. Experimental results strongly confirmthe effectiveness of the proposed
antenna design, establishing it as a competitive challenger for 5G technology.

Spectrum-driven acoustic metasurface for broadband noise control

To address the issue of broadband noise with tonal characteristics in indoor environments, a spectrum-driven acoustic metasurface (SAM) is proposed in this study. By combining the concept of coiled-up space with the synergetic effect between cascaded Helmholtz resonators, SAM with compact size can achieve targeted absorption of broadband noise with arbitrary tonal characteristics. Furthermore, an inverse design method based on genetic algorithms is proposed to regulate the sound absorption performance of SAM and its effectiveness is demonstrated through a case study on controlling transformer noise. Experimental results show that with a subwavelength thickness, SAM can efficiently absorb both the low-frequency noise of the transformer and the broadband noise of the cooling fans. The average sound absorption coefficient within the frequency range of 500–1000 Hz is 0.8, and reaches up to 0.85 at 100 Hz. This study provides theoretical guidance for targeted regulation of broadband noise with multiple low-frequency tonal components.

Severe cardiac and skeletal manifestations in DMD-edited microminipigs: an advanced surrogate for Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is an intractable X-linked muscular dystrophy caused by mutations in the DMD gene. While many animal models have been used to study the disease, translating findings to humans has been challenging. Microminipigs, with their pronounced physiological similarity to humans and notably compact size amongst pig models, could offer a more representative model for human diseases. Here, we accomplished precise DMD modification in microminipigs by co-injecting embryos with Cas9 protein and a single-guide RNA targeting exon 23 of DMD. The DMD-edited microminipigs exhibited pronounced clinical phenotypes, including perturbed locomotion and body-wide skeletal muscle weakness and atrophy, alongside augmented serum creatine kinase levels. Muscle weakness was observed as of one month of age, respiratory and cardiac dysfunctions emerged by the sixth month, and the maximum lifespan was 29.9 months. Histopathological evaluations confirmed dystrophin deficiency and pronounced dystrophic pathology in the skeletal and myocardial tissues, demonstrating that these animals are an unprecedented model for studying human DMD. The model stands as a distinct and crucial tool in biomedical research, offering deep understanding of disease progression and enhancing therapeutic assessments, with potential to influence forthcoming treatment approaches.

OpenCell: A low-cost, open-source, 3-in-1 device for DNA extraction.

High-cost DNA extraction procedures pose significant challenges for budget-constrained laboratories. To address this, we introduce OpenCell, an economical, open-source, 3-in-1 laboratory device that combines the functionalities of a bead homogenizer, a microcentrifuge, and a vortex mixer. OpenCell utilizes modular attachments that magnetically connect to a central rotating brushless motor. This motor couples to an epicyclic gearing mechanism, enabling efficient bead homogenization, vortex mixing, and centrifugation within one compact unit. OpenCell's design incorporates multiple redundant safety features, ensuring both the device's and operator's safety. Additional features such as RPM measurement, programmable timers, battery operation, and optional speed control make OpenCell a reliable and reproducible laboratory instrument. In our study, OpenCell successfully isolated DNA from Spinacia oleracea (spinach), with an average yield of 2.3 μg and an A260/A280 ratio of 1.77, demonstrating its effectiveness for downstream applications such as Polymerase Chain Reaction (PCR) amplification. With its compact size (20 cm x 28 cm x 6.7 cm) and lightweight design (0.8 kg), comparable to the size and weight of a laptop, OpenCell is portable, making it an attractive component of a 'lab-in-a-backpack' for resource-constrained environments in low-and-middle-income countries and synthetic biology in remote field stations. Leveraging the accessibility of 3D printing and off-the-shelf components, OpenCell can be manufactured and assembled at a low unit cost of less than $50, providing an affordable alternative to expensive laboratory equipment costing over $4000. OpenCell aims to overcome the barriers to entry in synthetic biology research and contribute to the growing collection of frugal and open hardware.

No Pain Device: Empowering Personal Safety with an Artificial Intelligence-Based Nonviolence Embedded System

This paper presents the development of a novel anti-violence device titled “no pAIn” (an acronym for Never Oppressed Protected by Artificial Intelligence Nonviolence system), which harnesses the power of artificial intelligence (AI). Primarily designed to combat violence against women, the device offers personal safety benefits for individuals across diverse demographics. Operating autonomously, it necessitates no user interaction post-activation. The AI engine conducts real-time speech recognition and effectively discerns genuine instances of aggression from non-violent disputes or conversations. Facilitated by its Internet connectivity, in the event of detected aggression, the device promptly issues assistance requests with real-time precise geolocation tracking to predetermined recipients for immediate assistance. Its compact size enables discreet concealment within commonplace items like candy wrappers, purpose-built casings, or wearable accessories. The device is battery-operated. The prototype was developed using a microcontroller board (Arduino Nano RP2040 Connect), incorporating an omnidirectional microphone and Wi-Fi module, all at a remarkably low cost. Subsequent functionality testing, performed in debug mode using the Arduino IDE serial monitor, yielded successful results. The AI engine exhibited exceptional accuracy in word recognition, complemented by a robust logic implementation, rendering the device highly reliable in discerning genuine instances of aggression from non-violent scenarios.

A compact, low‐loss, and wide passband ratio substrate integrated waveguide triplexer based on complementary split ring resonators for multiband applications

SummaryIn this paper, a design of a substrate‐integrated waveguide (SIW) triplexer with improved low‐loss performance, passband ratio, and compactness based on the complementary split ring resonator (CSRR) structure is presented. The proposed triplexer operates at three passbands of 6, 8, and 10 GHz that correspond to the passband ratios of 1.33 and 1.67. By appropriately designing square CSRRs on the surface of the SIW structure, the low‐loss and compact resonator filters below the cut‐off frequency of the SIW at each operation frequency can be realized. The wide passband ratio is obtainable by adjusting the dimensions of the T‐junction. The measured results show the minimum insertion losses of 1.5, 1.4, and 1.9 dB at 6, 8, and 10 GHz, respectively. In addition, the minimum measured return losses are −9.33, −11.3, and −12.4 dB at the corresponding three passbands. The measured isolation between output ports is better than −17 dB in the frequency range from 5 to 11 GHz. The measured results agree well with simulations which are conducted by the CST Microwave Studio simulator. The proposed triplexer is designed on a cost‐effective RO4003C substrate with a compact size of 35  25 mm2

High Directivity Microstrip Patch Antenna design using Binary Ebola Search Optimization for Radio Frequency Identification Application

Microstrip patch antenna has gained significant popularity in wireless communication field, because of its compact size, less profile, and ease of installation. It is widely used in various applications such as Radio-Frequency Identification (RFID) systems, where dependable and long-range communication is made possible by the great directivity and efficiency. In this manuscript, a High Directivity Microstrip Patch Antenna design using Binary Ebola Search Optimization for Radio Frequency Identification Application (MPA-RFID-BESO) is proposed.The design of microstrip patch antennas is the difficulty in achieving high directivity while maintaining compact size and low profile. This research explains design and application-specific optimisation of the Microstrip Patch Antenna (MPA) of biomedical utilizing Binary Ebola Search optimization (BESO) algorithm. Microstrip patch antenna is designed to function in double and multi band applications due to its low cost, light weight, and ease of installation. MPA is made with flawed ground construction to lessen cross-polarized radiation emitted by microstrip patches and to achieve the necessary radiation parameters. Here, the cost of the materials is reduced by using a liquid crystal polymer substrate, and aerial performance is enhanced by using the appropriate geometrical parameters. The small design of the BESO optimised improves the performance of antenna as 50mm×50mm compact size. The MATLAB program uses high frequency to do the simulation method. The proposed antenna design is a preferable option for applications involving Radio Frequency Identification (RFID). The performance metrics, such as radiation pattern, constant gain, directivity, bandwidth, and antenna efficiency and return loss are measured and compared to the existing techniques. The proposed MPA-BA-BESO design provides 10.51%, 12.85% and 16.04% higher bandwidth and 23.63%, 47.86% and 32.06% higher gain compared with existing designs, like Designing MPA utilizing Moth–Flame optimization approach (MPA-UWB-MFOA), Predicting Rectangular Patch Microstrip Antenna Dimension utilizing Machine Learning (MPA-ANN), Dual Band Antenna Design and Prediction of Resonance Frequency Utilizing Machine Learning Algorithms (DBAD-RF-CNN) respectively. The proposed technology serve as a better design alternative for microstrip patch antennas in communication systems to address biological applications.

Simulation of non-Newtonian fluid flow in a horizontal pipe

Microchannel reactors exhibit distinct gas-liquid two-phase flow behaviors compared to macro-scale channels, offering advantages like efficient heat and mass transfer, compact size, and low energy consumption. Sodium carboxymethyl cellulose (CMC) emerges as a potent stabilizer, enhancing mixing, homogenization and pipeline transport. Its judicious application reduces equipment strain, amplifies homogenization efficiency and finds diverse utility in food processing and beyond. However, incorrect employment bears the risk of compromised outcomes, potentially leading to product wastage. Consequently, investigating N2-CMC solution flow in microchannels holds paramount significance for elevating efficacy, minimizing usage, refining product quality and bolstering yield. In this study, we simulated the N2-CMC solution flow dynamics within an interleaved T-shaped microchannel using FLUENT which is a numerical simulation software. The simulation delved into alterations in gas-liquid two-phase flow patterns and pressure drops. We examined the impacts of liquid concentration and gas-liquid flow rate ratio on flow patterns, pressure drops and bubble lengths. The simulation results exhibited congruence with experimental data. Notably, elevated liquid concentrations correlated with higher pressure drops and elongated bubble lengths. Conversely, augmenting the gas-liquid flow rate ratio led to diminished pressure drops while elongating bubble lengths. These findings furnish insights into flow patterns and pressure drop behaviors for gas-non-Newtonian fluids within microchannels, forming a pivotal reference for microfluidic system design.

A Laplace operator-based active contour model with improved image edge detection performance

Active contour model (ACM) is an important branch in the field of image segmentation, since it adapts to different image types and scenes. However, traditional ACMs rely on local image information, which makes them sensitive to initial contours and time-consuming. In this paper, a Laplace operator based ACM (LOACM) with improved image edge detection performance is proposed. LOACM combines the global pre-fitting function which is constructed by using the image's second-order gradient information with the adaptive boundary indicator function to build a hybrid model. Its compact code size allows it to be executed on a wide range of edge devices. To substantiate the segmentation capability of the LOACM model, the BSD500 dataset was utilized for experimentation. The results indicate that LOACM exhibits excellent performance, with average IOU and DSC scores of 0.861 and 0.924 respectively. Additionally, it consistently handles processes within an average time of less than 0.3s, significantly less than that of comparative models, providing compelling evidence of LOACM's exceptional efficiency and precision.

Insights into the chemistry of Kubas’ chromium dihydrogen complexes

The structures of the complexes Cr(CO)3(PR3)2, (3) R = cyclohexyl and (4) isopropyl and their labile dihydrogen adducts Cr(η2-H2)(CO)3(PR3)2 (1) R = cyclohexyl and (2) isopropyl are calculated using density functional theory and compared to known structures of 3, Cr(η2-HC-CyPCy2)(CO)3(PCy3) (CSD code JOHNOJ) with an agostic CHCr interaction, and of 2, Cr(η2-H2)(CO)3(PiPr3)2 (CSD LEYCOH) with a very short HH distance. The TPSS functional with Grimme D3 dispersion, with a def2-TZVP basis set on all atoms and with the PCM solvent model for tetrahydrofuran (THF) reproduces fairly accurately the geometries, available vibrational spectra, and enthalpy of dihydrogen coordination in THF solution from literature experiments while other computational settings do not. This is a rare example of the calibration of theory with experiment for the Gibbs energy change in a solution phase reaction involving dihydrogen gas. The agostic form of the molecule is favoured in the crystal by intermolecular CHHC interactions as illustrated using Hirshfeld surface analysis and by the more compact size of this conformation.

End-to-end optimization of single-shot monocular metasurface camera for RGBD imaging

RGBD cameras that capture color and depth information have a wide range of applications such as robotics, autonomous driving, and cons umer electronics. Traditional RGBD imaging usually requires multi-cameras or extra active illumination which inevitably leads to bulky or complex imaging systems, hindering the growing demand for compact integrated optical devices. Optical metasurface have emerged as a powerful substitute to the traditional diffractive optical element due to the superior dispersion manipulation and extremely compact size. However, it is still a great challenge to realize a single-shot monocular metasurface camera, due to the strong and unignorable wavelength-dependent aberrations. In this work, we demonstrate an end-to-end compact single-shot monocular metasurface camera for RGBD imaging. By utilizing end-to-end joint optimization framework to learn metasurface physical structure in conjunction with deep neural networks reconstruction algorithm, the multidimensional light field information RGBD of a scene in a single shot can be reconstructed within a depth range of 0.5m. Compared with traditional lens-based RGBD imaging, our proposed metasurface-based imaging achieves an improvement of about 2dB in chromatic imaging and a 4 times increase in depth estimation accuracy. Our proposed scheme could facilitate the further development of the intelligent computational meta-optics in diverse fields ranging from machine vision to biomedical imaging.

Design and experimental validation of a broadband multi-modal coupled capsule-shaped transducer for underwater acoustics

This paper introduces a novel approach to expand the working frequency band of underwater acoustic transducers through multi-modal coupling. We designed a broadband multi-modal coupled piezoelectric capsule-shaped transducer structure by leveraging the advantages of conventional piezoelectric spherical-shell and piezoelectric cylindrical-tube transducers. First, the finite element method (FEM) was employed to scrutinize the influence of key structural parameters on the acoustic performance of the capsule-shaped transducer, thereby establishing the foundation for the final transducer design. Subsequently, the designed transducer was characterized through modal analysis and harmonic response analysis of electrical-mechanical-acoustical multiphysics field coupling. Finally, a prototype of the capsule-shaped transducer was fabricated and measured, with the results compared with those of a spherical-shell transducer. A comparative analysis of the measured outcomes revealed that the capsule-shaped transducer exhibits coupling among three modes within the frequency range of 10 kHz to 30 kHz. The transmitting voltage response (TVR) values exceeded 143.5 dB, reaching a maximum of 151.9 dB, and the working frequency bandwidth achieved 18 kHz. Compared with the spherical-shell transducer, the average TVR value demonstrates a 3.7 dB improvement, and the bandwidth exhibited an 8.4 % increase. According to the experimental findings, the proposed capsule-shaped piezoelectric transducer offers advantages such as high voltage response, a broad working frequency band, compact size, low weight, and easy installation. This technology can be further applied to small underwater platforms, enhancing their acoustic detection range and spatial coverage performance.

Microstrip Planar Antennas for C-Band Wireless Applications

In recent years, wireless communications have evolved significantly, and many mobile devices have reduced in size. The antennas used in mobile terminals must be lowered in size to fulfil the downsizing standards. Planar antennas, like microstrip and printed antennas, have a low profile, compact size, and conformability to mounting hosts, making them particularly desirable candidates for achieving these needs. Additionally, planar antennas are also being used in communication devices for 2.4 GHz (2400 – 2484 MHz) and 5.2 GHz wireless local area network (WLAN) systems (5150). In wireless applications, an antenna is a crucial component. At the transmitter, it transforms electrical signals into RF signals, and at the receiver, it converts RF signals to electrical signals. The patch inside the antenna is made of a conducting material such as Cu (Copper) or Au (Gold), and it can be rectangular, round, triangular, or elliptical. Two unique designs of microstrip planar antennas with an operating frequency of 5.2 GHz having S11 parameters as -16.0 dB and -15.7 dB have been offered and their performance has been studied in this research article.