Search Results (4,294)

Compared with traditional piezoelectric transducers, Capacitive Micromachined Ultrasonic Transducers (CMUTs) have advantages such as better impedance matching with air, smaller size, lighter weight, higher sensitivity, and ease of array formation. Acoustic temperature measurement is a technology that utilizes the relationship between sound velocity and temperature to achieve non-contact temperature detection, with advantages such as fast response and non-invasiveness. CMUT-based acoustic temperature field measurement can achieve temperature detection in situations with narrow spaces, portability, and high measurement accuracy. This paper investigates an air-coupled CMUT device for acoustic temperature measurement, featuring a resonant frequency of 220 kHz, and composed of 16 × 8 cells. The design and fabrication of the CMUT array were completed, and the device characteristics were tested and characterized. A temperature field measurement method using mechanical scanning was proposed. A temperature measurement experimental system based on CMUT devices was constructed, achieving preliminary measurement of acoustic transmission time in both uniform and non-uniform temperature fields. Using a temperature field reconstruction algorithm, the measurement and imaging of the temperature field above an electric heating wire were accomplished and compared with the thermocouple-based temperature measurement experiment. The experimental results verified the feasibility of CMUT devices for non-contact temperature field measurement. Full article

Liquid metal (LM), which possesses unique material properties such as excellent flexibility, high thermal and electrical conductivities, and biocompatibility, has demonstrated broad application potential in the fields of intelligent manufacturing, flexible electronics, and biomedical engineering. This paper presents a systematic review of recent advances in multifunctional LM materials for biomimetic applications, with a focus on 3D printing, catalysis, sensing, and biomedical technologies. Through advanced 3D printing techniques—including direct writing, embedded printing, and extrusion/infiltration—LM has been effectively utilized in the fabrication of high-precision electronic components. In catalysis, LM-based catalysts exhibit superior performance in energy conversion and environmental remediation due to their high catalytic activity and selectivity. Moreover, LM has made notable progress in the development of high-performance sensors and biomedical devices, contributing significantly to the advancement of health monitoring and intelligent diagnostic and therapeutic technologies. This review aims to provide theoretical insights and technical references for further research and engineering applications of liquid metals. Full article

High−entropy alloys (HEAs) have shown great promise for applications in extreme service environments due to their exceptional mechanical properties and thermal stability. However, traditional alloy design often struggles to balance multiple properties such as strength and ductility. Constructing heterogeneous microstructures has emerged as an effective strategy to overcome this challenge. With the rapid advancement of additive manufacturing (AM) technologies, their unique ability to fabricate complex, spatially controlled, and non−equilibrium microstructures offers unprecedented opportunities for tailoring heterostructures in HEAs with high precision. This review highlights recent progress in utilizing AM to engineer heterogeneous microstructures in high−performance HEAs. It systematically examines the multiscale heterogeneities induced by the thermal cycling effects inherent to AM techniques such as selective laser melting (SLM) and electron beam melting (EBM). The review further discusses the critical role of these heterostructures in enhancing the synergy between strength and ductility, as well as improving work− hardening behavior. AM enables the design−driven fabrication of tailored microstructures, signaling a shift from traditional “performance−driven” alloy design paradigms toward a new model centered on “microstructural control”. In summary, additive manufacturing provides an ideal platform for constructing heterogeneous HEAs and holds significant promise for advancing high−performance alloy systems. Its integration into alloy design represents both a valuable theoretical framework and a practical pathway for developing next−generation structural materials with multiple performance attributes. Full article

The constitutive modelling of granular soils has been a long-standing research subject in geotechnical engineering, and machine learning (ML) has recently emerged as a promising tool for achieving this goal. This paper proposes two recurrent neural networks, namely, the Gated Recurrent Unit Neural Network (GRU-NN) and the Long Short-Term Memory Neural Network (LSTM-NN), which utilize input parameters such as the initial void ratio, initial fabric anisotropy, uniformity coefficient, mean particle size, and confining pressure to establish the high-dimensional relationships of granular soils from micro to macro levels subjected to triaxial shearing. The research methodology consists of several steps. Firstly, 200 numerical triaxial tests on idealized granular soils comprising polydisperse spherical particles are performed using the discrete element method (DEM) simulation to generate datasets and to train and test the proposed neural networks. Secondly, LSTM-NN and GRU-NN are constructed and trained, and their prediction performance is evaluated by the mean absolute percentage error (MAPE) and R-square against the DEM-based datasets. The extremely low error values obtained by both LSTM-NN and GRU-NN indicate their outstanding capability in predicting the constitutive behaviour of idealized granular soils. Finally, the trained ML-based models are applied to predict the constitutive behaviour of a miniature glass bead sample subjected to triaxial shearing with in situ micro-CT, as well as to two extrapolated test sets with different initial parameters. The results show that both methods perform well in capturing the mechanical responses of the idealized granular soils. Full article

Diffusion-weighted magnetic resonance (DWMR) images were acquired using a custom-designed, 3D-printed breast-mimicking phantom. The smoothing factor of the non-local means (NLM) algorithm was then optimized for noise reduction. Phantoms were fabricated using polylactic acid, polyethylene terephthalate, and various concentrations of polyvinylpyrrolidone. DWMR images were obtained across b-values ranging from zero to 2000 s/mm². Based on image contrast, the NLM algorithm was applied to the b = 1000 s/mm² image, testing smoothing factors from 0.001 to 0.150. The NLM algorithm’s performance was quantitatively evaluated using a single DWMR image acquired from this custom phantom. At the optimized smoothing factor, the signal-to-noise ratio (SNR) improved from 96.87 ± 3.42 to 215.81 ± 4.18, and the contrast-to-noise ratio (CNR) from 43.63 ± 2.97 to 131.98 ± 3.56, representing 2.22-fold and 3.02-fold enhancements, respectively. No formal statistical tests were conducted as the analysis was based on a single acquisition. The optimized NLM algorithm also outperformed conventional denoising methods—median, Wiener, and total variation—in both noise suppression and contrast preservation. These findings suggest that the NLM algorithm with optimized parameters is likely to be more effective than existing approaches for enhancing breast DWMR image quality. However, further validation using in vivo patient datasets is essential to confirm its diagnostic utility and clinical generalizability because of the absence of tissue heterogeneity, motion, and physiological noise in the phantom environment. Full article

Silicon carbide (SiC) has become the material of choice for precision optical systems due to its exceptional optical characteristics. However, conventional anti-reflection strategies for SiC components predominantly utilize deposited thin-film coatings, which are frequently compromised by insufficient environmental robustness and long-term stability concerns. To overcome these limitations, direct nanostructuring of SiC substrates has emerged as a promising alternative solution. This work introduces an innovative graded-index microcone array design fabricated on SiC substrates, achieving superior broadband anti-reflection performance. Our two-step fabrication methodology comprises plasma-induced formation of tunable nanofiber etch masks through controlled argon bombardment parameters, followed by precision reactive ion etching (RIE) for microcone array formation. By systematically varying plasma exposure duration, we demonstrate precise control over nanofiber mask morphology, which in turn enables the fabrication of height-optimized SiC microcone arrays. The resulting structures exhibit exceptional optical performance, achieving an ultra-low average reflectivity of 2.25% across the spectral range of 2.5–8 μm. This breakthrough fabrication technique not only extends the available toolbox for SiC micro/nanofabrication but also provides a robust platform for next-generation optical applications. Unlike conventional thin-film approaches, our nanostructuring method preserves the intrinsic mechanical and environmental durability of the SiC substrate while delivering a favorable optical performance. Full article

A low-profile beam-scanning antenna array for cost-effective 5G millimeter-wave (mmWave) applications is proposed in this work. The array features a compact single-layer substrate structure while achieving a wide operating bandwidth covering the 5G n257 band (26.5–29.5 GHz). A novel antenna element is first designed and analyzed, employing a metallic rectangular patch with shorting pins as the radiator, excited through a modified coplanar waveguide (CPW) feeding structure. Based on this element, four-element and eight-element linear arrays are developed with an overall profile of only 0.07 λ at 28 GHz and fabricated to experimentally assess beam-scanning performance. To accurately characterize and validate the radiation behavior, an mmWave beam box system is utilized for pattern measurements. The results demonstrate that the fabricated arrays achieve an impedance bandwidth fully covering the 5G n257 band with VSWR < 2, while the measured beam-scanning performance closely agrees with simulations. These findings confirm that the proposed design and its extensions offer strong potential for practical integration into future 5G mmWave communication devices. Full article

Aluminum nitride (AlN) ceramics exhibit exceptional properties that render them highly valuable for diverse industrial applications. However, conventional manufacturing techniques encounter significant challenges in fabricating complex AlN components with precise geometries. To address these limitations, digital light processing (DLP) has emerged as a promising additive manufacturing approach for AlN ceramics. This study presents a systematic investigation of the monomer composition in the photopolymer resin system through a comprehensive experimental evaluation. The results demonstrate that an optimized mixture of monomers ACMO (56.7 wt%), DEGDA (2.7 wt%), and TMPTA (40.6 wt%) yields photopolymer resin with superior comprehensive performance. Utilizing this optimized formulation, a 50 vol% solid loading AlN ceramic slurry was successfully prepared, and subsequently, dense AlN ceramic components were fabricated through DLP. This provides an important basis for optimizing the slurry preparation of AlN ceramic fabrication based on DLP 3D printing. Full article

Optical phase modulation is essential for a wide range of silicon photonic integrated circuits used in communication applications. In this study, an optical phase shifter utilizing photo-elastic effects is proposed, where mechanical stress is induced by electrostatic micro-electro-mechanical systems (MEMS) with actuators arranged in a comb drive configuration. The design incorporates suspended serpentine silicon nitride (SiN) optical waveguides. Through extensive numerical simulations, it is shown that the change in the effective refractive index (n_eff) of the optical waveguide is a function of the voltage applied to the electrostatic actuators and that such n_eff tuning can be achieved for a broad range of wavelengths. Implemented within one arm of an unbalanced Mach–Zehnder interferometer (MZI), the phase shifter achieves a phase change of π when the stressed optical path measures 4.7 mm, and the actuators are supplied with 80 V DC and consume almost no power. This results in a half-wave voltage-length product (V_πL) of 37.6 V·cm. Comparative analysis with contemporary optical phase shifters highlights the proposed design’s superior power efficiency, compact footprint, and simplified fabrication process, making it a highly efficient component for reconfigurable MEMS-based silicon nitride photonic integrated circuits. Full article

Fiber-chip couplers play an important role in the field of on-chip all-optical ultrasound detection; however, they have received limited attention in research. Here, we present an on-chip photoresin coupler fabricated via two-photon lithography, combining the benefits of compact size, wide bandwidth, low loss, and robust coupling. Utilizing a high-refractive-index photoresin medium, we achieved transmission efficiencies better than −1.3 dB in water environments within a 1528–1567 nm bandwidth. Alignment errors were constrained to ±2.5 μm laterally and 20 μm axially, with angular deviations exceeding ±3° at a −1 dB loss. Its sturdy structure facilitates 5–30 MHz ultrasound detection in liquid environments through phase-shifted Bragg grating. Full article

To develop a new porous metal for aerostatic bearing, herein, novel porous thin plates (PTPs) with micron-scale porous structures are fabricated. The pore size distribution and air permeability of PTPs are measured. A tensile test is carried out and the fractography is observed. The load capacity and stiffness of aerostatic bearings utilizing PTPs as porous restrictors are tested. The results show that the phenomenon of the uneven distribution of powders can be significantly improved by decreasing the roller speed. Fine powder porous thin plates (FPTPs) effectively balance permeability and mechanical properties, achieving an ultimate tensile strength of 157 MPa while maintaining favorable permeability, significantly exceeding existing porous restrictors. Aerostatic bearings employing PTPs as restrictors demonstrate substantial load capacity and stiffness. Notably, aerostatic bearings utilizing coarse powder porous thin plates (CPTPs) as restrictors deliver 511 N load capacity and 22 N/μm stiffness with a considerably smaller porous restrictor area. It is worth noting that the novel PTPs not only exhibit a straightforward and environmentally friendly manufacturing process but also preserve the micron-scale porous structure while meeting the practical requirements of aerostatic bearings, holding significant promise for gas lubrication applications. Full article

Natural polymers, such as gelatin, offer a sustainable, green, and versatile alternative for developing proton exchange membranes in low-temperature fuel cell applications. They provide a balance of biocompatibility, flexibility, and ionic conductivity. In this work, gelatin-based composite membranes are reported. The membranes were fabricated and modified with various additives, including ionic liquids (ILs), polyethylene glycol (PEG), and glycerol, to enhance their electrochemical and mechanical properties. The proton conductivity of the pure gelatin membrane was relatively low at 1.0368 × 10⁻⁴ Scm⁻¹; however, the incorporation of IL ([DEMA][OMs]) significantly improved it, with the gelatin/0.2 g IL membrane achieving the highest conductivity of 4.181 × 10⁻⁴ Scm⁻¹. The introduction of PEG and glycerol also contributed to enhanced conductivity and flexibility. The water uptake analysis revealed that IL-containing membranes exhibited superior hydration properties, with the highest water uptake recorded for the gelatin/0.2 g glycerol/0.2 g IL membrane, which was found to be very high (906.55%). The results showed that the combination of IL and PEG provided enhanced proton transport and mechanical stability (as examined visually), making these membranes promising candidates for fuel cell applications. Therefore, this study underscores the importance of bio-based materials by utilizing gelatin as a sustainable, biodegradable polymer, supporting the transition toward greener energy materials. The findings demonstrate that modifying gelatin with conductivity-enhancing and plasticizing agents can significantly improve its performance, paving the way for bio-based proton exchange membranes with improved efficiency and durability. Full article

Due to the rapid advancements in coordinate measuring systems, data processing software, and additive manufacturing (AM) techniques, it has become possible to create copies of existing models through the reverse engineering (RE) process. However, the lack of precise estimates regarding the accuracy of the RE process—particularly at the measurement, reconstruction, and computer-aided design (CAD) modeling stages—poses significant challenges. Additionally, the assessment of dimensional and geometrical errors during the manufacturing stage using AM techniques limits the practical implementation of product replicas in the industry. This paper provides an estimation of the errors encountered in the RE process and the AM stage of various models. It includes examples of an electrical box, a lampshade for a standing lamp, a cover for a vacuum unit, and a battery cover. The geometry of these models was measured using a GOM Scan 1 (Carl Zeiss AG, Jena, Germany). Following the measurement process, data processing was performed, along with CAD modeling, which involved primitive detection, profile extraction, and auto-surface methods using Siemens NX 2406 software (Siemens Digital Industries, Plano, TX, USA). The models were produced using a Fortus 360-mc 3D printer (Stratasys, Eden Prairie, MN, USA) with ABS-M30 material. After fabrication, the models were scanned using a GOM Scan 1 scanner to identify any manufacturing errors. The research findings indicated that overall, 95% of the points representing reconstruction errors are within the maximum deviation range of ±0.6 mm to ±1 mm. The highest errors in CAD modeling were attributed to the auto-surfacing method, overall, 95% of the points are within the average range of ±0.9 mm. In contrast, the lowest errors occurred with the detect primitives method, averaging ±0.6 mm. Overall, 95% of the points representing the surface of a model made using the additive manufacturing technology fall within the deviation range ±0.2 mm on average. The findings provide crucial insights for designers utilizing RE and AM techniques in creating functional model replicas. Full article

The primary objective of the presented study is to develop a comprehensive system for the acquisition of surface electromyographic (sEMG) data and to perform time–frequency analysis aimed at extracting discriminative features for the classification of hand gestures intended for the control of a simplified bionic hand prosthesis. The proposed system is designed to facilitate precise finger gesture execution in both prosthetic and robotic hand applications. This article outlines the methodology for multi-channel sEMG signal acquisition and processing, as well as the extraction of relevant features for gesture recognition using artificial neural networks (ANNs) and other well-established machine learning (ML) algorithms. Electromyographic signals were acquired using a prototypical LPCXpresso LPC1347 ARM Cortex M3 (NXP, Eindhoven, Holland) development board in conjunction with surface EMG sensors of the Gravity OYMotion SEN0240 type (DFRobot, Shanghai, China). Signal processing and feature extraction were carried out in the MATLAB 2024b environment, utilizing both the Fourier transform and the Hilbert–Huang transform to extract selected time–frequency characteristics of the sEMG signals. An artificial neural network (ANN) was implemented and trained within the same computational framework. The experimental protocol involved 109 healthy volunteers, each performing five predefined gestures of the right hand. The first electrode was positioned on the brachioradialis (BR) muscle, with subsequent channels arranged laterally outward from the perspective of the participant. Comprehensive analyses were conducted in the time domain, frequency domain, and time–frequency domain to evaluate signal properties and identify features relevant to gesture classification. The bionic hand prototype was fabricated using 3D printing technology with a PETG filament (Spectrum, Pęcice, Poland). Actuation of the fingers was achieved using six MG996R servo motors (TowerPro, Shenzhen, China), each with an angular range of ${180}^{\circ }$, controlled via a PCA9685 driver board (Adafruit, New York, NY, USA) connected to the main control unit. Full article

Advanced engineering materials are in high demand for a combination of tailored properties in a single material. Titanium with aluminum alloys is widely used to prepare pistons and knee joints due to its high strength and abundant availability. The primary focus of the study was to utilize an eco-friendly composite material with low cost and a simple production process. Ti–48Al–2Cr–2Nb with molybdenum disulfide was added as reinforcement in varying percentages, fabricated using the squeeze casting production technique. The dry sliding wear test was performed. Adding 4% molybdenum disulfide to Ti–48Al–2Cr–2Nb enhanced its mechanical properties and wear resistance by 57%. Full article