Search Results (11,544)

Micromixers are important devices used in many fields for various applications which provide high mixing efficiencies and reduce the amount of reagents and samples. In addition, effective premixing of reactants is essential for obtaining high reaction rates. In order to further improve the mixing performance, three-dimensional numerical simulations and optimizations of the flow and mixing characteristics within a variable cross section T-shaped micromixer were carried out. The effects of the geometric parameters containing channel diameter, channel shape, channel contraction and expansion ratio, and number of expansion units on the mixing were investigated with the evaluation criteria of mixing index and performance index. The optimized geometric parameters of the channel were a diameter of 0.2 mm, the shape of Sem channel, an expansion ratio of 1:3, and a number of expansion units of 7, respectively. It can be showed that the mixing efficiency of the optimized micromixer was greatly improved, and the mixing index at different velocities could reach up to more than 0.98. Full article

In this work, we present a wideband on-wafer characterization technique for InAlAs/InGaAs/InAs InP-based high-electron mobility transistors (HEMTs) using an optimized multiline Thru-Reflect-Line (mTRL) calibration kit. Our goal is to directly extract transition frequency fT and maximum frequency of oscillation fmax values from S-parameters measurements with frequencies up to 1.1 THz and overcome the limitations of the traditional 20 dB/dec extrapolation method using lower-frequency band measurements. Indeed, as the state-of-the-art transistors now exhibit cutoff frequencies exceeding 1 THz, standard low-frequency extrapolation methods become increasingly inaccurate. Full-wave electromagnetic simulations were used to design low-loss coplanar waveguide (CPW) access structures with stable impedance and minimal parasitic effects. These structures were co-fabricated with HEMTs and calibration standards on the same InP substrate. The 2-finger transistor with a 80 nm gate length exhibits a directly measured fT = 320 GHz and fmax = 800 GHz. The technique showed high consistency across six frequency bands and confirms that direct broadband measurement with mTRL improves accuracy. This work highlights the metrological strength of mTRL-based setups for next-generation THz device characterization. Full article

As a common signal sensing device in pulsed eddy current detection, coil sensors often have parameter offset problems in practical applications. The error in the receiving coil parameters will have a great impact on the early signal. In order to ensure the accuracy of the early signal, this paper first analyzes the response characteristics of the receiving coil and the influence of the coil parameters on the accuracy of signal deconvolution and establishes the mathematical relationship between the response signal and the characteristic parameters, and between the characteristic parameters and the receiving coil parameters under active underdamped oscillation. Subsequently, the parameter feature extraction errors under different state switching capacitors were compared through simulation analysis, the state switching capacitor value was determined, and the receiving coil parameter solution method based on the Levenberg–Marquardt (LM) algorithm was determined based on the parameter feature extraction results. The experimental results demonstrate that the proposed method achieves a capacitance estimation error of just 0.0159% and an inductance error of 0.158%, effectively minimizing early signal distortion and enabling precise identification of receiving coil parameters. Full article

In the field of high-temperature in situ sensing, highly reflective Fabry–Perot (F-P) cavity mirrors with thermal stress matching are urgently needed. The quartz-based volume Bragg grating (VBG) can replace the dielectric high-reflection film to prepare a high-temperature and high-precision F-P cavity sensitive unit by virtue of the integrated structure of homogeneous materials. The reflectivity of the VBG is a key parameter determining the performance of the F-P cavity, and its accurate measurement is very important for the pre-evaluation of the device’s sensing ability. Based on the reflectivity measurement of quartz-based VBG with a large aspect ratio, a free-space optical path reflective measurement system is proposed. The ZEMAX simulation is used to optimize the optical transmission path and determine the position of each component when the optimal spot size is achieved. After completing the construction of the VBG reflectivity measurement system, the measurement error is calibrated by measuring the optical path loss, and the maximum error is only 1.2%. Finally, the reflectivity of the VBG measured by the calibrated system is 30.84%, which is basically consistent with the multi-physical field simulation results, showing a deviation as low as 0.85%. The experimental results fully verify the availability and high measurement accuracy of the reflectivity measurement system. This research work provides a new method for testing the characteristics of micron-scale grating size VBGs. Additionally, this work combines optical characterization methods to verify the good effect of VBG preparation technology, providing core technical support for the realization of subsequent homogeneous integrated Fabry–Perot cavity sensors. Furthermore, it holds important application value in the field of optical sensing and micro-nano integration. Full article

In this paper, a novel enhancement-mode β-Ga₂O₃-based FinFET structure with a gate formed by the NiO/β-Ga₂O₃ heterojunction named HJ-FinFET has been proposed, and the excellent performance of the device has also been demonstrated. The primary operational mechanism of this structure involves integrating p-type NiO on both sides of the fin-shaped channel, which forms p-n junctions with β-Ga₂O₃. The depletion regions thus generated are utilized to establish electron channels, enabling enhancement-mode operation. The reverse p-NiO/n-Ga₂O₃ heterojunction diode is integrated to reduce the reverse free-wheeling loss. Compared with the conventional devices, the threshold voltage of the HJ-FinFET is greatly improved, and normally off operation is realized, showing a positive threshold voltage of 2.14 V. Meanwhile, the simulated breakdown voltage of the HJ-FinFET reaches 2.65 kV with specific on-resistance (R_on,sp) of 2.48 mΩ·cm² and the power figure of merit (PFOM = BV²/R_on,sp) reaches 2840 MW/cm², respectively. In addition, the influence of the doping concentration of the heterojunction layer constituting the gate, the doping concentration of the drift layer, and the channel width on the electrical characteristics of the devices were focused on. This structure provides a feasible idea for high-performance β-Ga₂O₃-based FinFET. Full article

In order to solve the problem that it is difficult to take into account the performance constraints between the core functions of insulation, current flow and arc extinguishing of high-voltage vacuum circuit breakers at the same time, this paper proposes a flexible control strategy for the motor operating mechanism of high-voltage vacuum circuit breakers. The relationship between the rotation angle of the motor and the linear displacement of the moving contact of the circuit breaker is analyzed, and the ideal dynamic curve is planned. The motor drive control device is designed, and the phase-shifted full-bridge circuit is used as the boost converter. The voltage and current double closed-loop sliding mode control strategy is used to simulate and verify the realization of multi-stage and stable boost. The experimental platform is built and the experiment is carried out. The results show that under the voltage conditions of 180 V and 150 V, the control range of closing speed and opening speed is increased by 31.7% and 25.9% respectively, and the speed tracking error is reduced by 51.2%. It is verified that the flexible control strategy can meet the ideal action curve of the operating mechanism, realize the precise control of the opening and closing process and expand the control range. The research provides a theoretical basis for the flexible control strategy of the high-voltage vacuum circuit breaker operating mechanism, and provides new ideas for the intelligent operation technology of power transmission and transformation projects. Full article

Star trackers are critical electro-optical devices used for satellite attitude determination, typically tested using Optical Ground Support Equipment (OGSE). Within the POR FESR 2014–2020 program (funded by Regione Toscana), we developed MINISTAR, a compact electro-optical prototype designed to generate synthetic star fields in apparent motion for realistic ground-based testing of star trackers. MINISTAR supports simultaneous testing of up to three units, assessing optical, electronic, and on-board software performance. Its reduced size and weight allow for direct integration on the satellite platform, enabling testing in assembled configurations. The system can simulate bright celestial bodies (Sun, Earth, Moon), user-defined objects, and disturbances such as cosmic rays and stray light. Radiometric and geometric calibrations were successfully validated in laboratory conditions. Under the PR FESR TOSCANA 2021–2027 initiative (also funded by Regione Toscana), the concept was further developed into STARLITE (STAR tracker LIght Test Equipment), a next-generation OGSE with a higher Technology Readiness Level (TRL). Based largely on commercial off-the-shelf (COTS) components, STARLITE targets commercial maturity and enhanced functionality, meeting the increasing demand for compact, high-fidelity OGSE systems for pre-launch verification of attitude sensors. This paper describes the working principles of a generic system, as well as its main characteristics and the early advancements enabling the transition from the initial MINISTAR prototype to the next-generation STARLITE system. Full article

Predicting absolute values of hemolysis using the power law model to guide medical device design is hampered by uncertainties stemming from four sources of model inputs: incoming/upstream velocity profiles, blood viscosity models, power law hemolysis coefficients, and obtaining accurate stress exposure times. Amidst all these uncertainties, enabling rapid assessments and predictions of relative hemolysis would still be valuable for evaluating device design prototypes. Towards achieving this objective, hemolysis data from the Eulerian modeling framework was first generated from computational fluid dynamics simulations encompassing five blood viscosity models, four sets of hemolysis power law coefficients, fully developed as well as developing velocity flow conditions, and a wide range of shear stresses, strain rates, and stress exposure times. Corresponding hemolysis predictions were also made in a Lagrangian framework via numerical integration of shear stress and residence time spatial variations under the assumption of fully developed Newtonian fluid flow. Absolute hemolysis predictions (from both frameworks) were proportional to each other and independent of the blood viscosity model. Further, relative hemolysis trends were not dependent on the hemolysis power law coefficients. However, accuracy in wall shear stresses in developing flow conditions is necessary for accurate relative hemolysis assessments. 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

In dense urban environments and large-scale events, Internet infrastructure often becomes overloaded due to high communication demand. Many of these communications are local and short-lived, exchanged between users in close proximity but still relying on global infrastructure, leading to unnecessary network stress. In this context, delay-tolerant networks (DTNs) offer an alternative by enabling device-to-device (D2D) communication without requiring constant connectivity. However, DTNs face significant challenges in routing due to unpredictable node mobility and intermittent contacts, making reliable delivery difficult. Considering these challenges, this paper presents a hybrid Beyond 5G (B5G) DTN architecture to provide private context-aware routing in dense scenarios. In this proposal, dynamic contextual notifications are shared among relevant local nodes, combining federated learning (FL) and edge artificial intelligence (AI) to estimate the optimal relay paths based on variables such as mobility patterns and contact history. To keep the local FL models updated with the evolving context, edge nodes, integrated as part of the B5G architecture, act as coordinating entities for model aggregation and redistribution. The proposed architecture has been implemented and evaluated in simulation testbeds, studying its performance and sensibility to the node density in a realistic scenario. In high-density scenarios, the architecture outperforms state-of-the-art routing schemes, achieving an average delivery probability of 77%, with limited latency and overhead, demonstrating relevant technical viability. Full article

The evolution of sixth-generation (6G) networks enables transformative edge Artificial Intelligence of Things (AIoT) applications but introduces critical security vulnerabilities during model transmission between the central server and edge devices (e.g., unmanned aerial vehicles). Traditional approaches fail to jointly optimize model accuracy and physical layer security against eavesdropping. To address this gap, we propose a novel dynamic user selection framework that integrates three key innovations: (1) closed-form secrecy outage probability derivation for Rayleigh fading channels, (2) a Secure Model Accuracy (SMA) metric unifying recognition accuracy and secrecy outage probability, and (3) an alternating optimization algorithm for joint model–bandwidth selection under secrecy constraints. Comprehensive simulations demonstrate 22% SMA gains over baselines across diverse channel conditions and eavesdropper capabilities, resolving the fundamental accuracy–security tradeoff for trustworthy edge intelligence. Full article

With the large-scale integration of renewable energy devices into the power grid, the voltage stability of the renewable energy base is becoming increasingly weak, and the problem of transient overvoltage is becoming increasingly severe. Grid-forming (GFM) converters can provide strong voltage support. When GFM converters are paralleled with grid-following (GFL) converters, they can effectively reduce transient overvoltage. However, hybrid systems involve many parameters and exhibit complex dynamics, making assessment of transient overvoltage difficult. To address this, this paper first uses Thevenin’s theorem to reduce the renewable transmission system to an equivalent model. Next, the voltage assessment of the hybrid system is analyzed across the pre-fault, mid-fault, and post-fault stages of a short-circuit fault. Then, based on the characteristics of a phase-locked loop (PLL), this paper innovatively derives an assessment method for transient overvoltage at the common coupling point (PCC) under different PLL stability conditions. Additionally, the influence of GFL converter parameters, GFM converter parameters, the GFM capacity ratio on transient overvoltage, and the external system reactance are analyzed. Finally, the proposed evaluation method and factor analysis are validated through electromechanical transient simulation using the simulation software STEPS v2.2.0. Full article

With the widespread application of multilevel inverters, device losses have become a critical area of research. A key limitation of conventional three-level discontinuous pulse width modulation (DPWM) strategies is their inability to maintain switching device clamping during the peak intervals of the load current, especially under varying load power factor conditions, thereby reducing switching losses. This paper proposes an improved three-level power factor adaptive DPWM (PFA-DPWM) strategy that minimizes switching losses by clamping the power devices during the one-third fundamental period of maximum load current. First, a unified mathematical model of DPWM strategies is established. Theoretical analysis demonstrates that phase disposition (PD) carrier modulation for three-level inverter exhibits superior line voltage harmonic characteristics. Based on this, a theoretical comparison of switching losses and harmonic distortion for various DPWM schemes is conducted. The proposed PFA-DPWM control strategy has the minimum switching loss without compromising harmonic performance. The efficacy and validity of the proposed strategy are confirmed by comprehensive simulation and experimental results. Full article

The global market for fog computing is expected to reach USD 6385 million by 2032. Modern enterprises rely on fog computing since it offers computational resources at edge devices through decentralized computation mechanisms. One of the crucial components of fog computing is the proper placement of applications on fog nodes (edge devices, Internet of Things (IoT)) for servicing. Large-scale, geographically distributed fog networks and heterogeneity of fog nodes make application placement a challenging task. Quantile Temporal Difference Learning (QTDL) is a promising distributed form of a reinforcement learning algorithm. It is superior compared to traditional reinforcement learning as it learns the act of prediction based on the full distribution of returns. QTDL is enriched by a small language model (SLM), which results in low inference latency, reduced costs of operation, and also enhanced rates of learning. The SLM, being a lightweight model, has policy-shaping capability, which makes it an ideal choice for the resource-constrained environment of edge devices. The data-driven quantiles of temporal difference learning are blended with the informed heuristics of the SLM to prevent quantile loss and over- or underestimation of the policies. In this paper, a novel SLM-guided QTDL framework is proposed to perform task scheduling among fog nodes. The proposed framework is implemented using the iFogSim simulator by considering both certain and uncertain fog computing environments. Further, the results obtained are validated using expected value analysis. The performance of the proposed framework is found to be satisfactory with respect of the following performance metrics: energy consumption, makespan time violations, budget violations, and load imbalance ratio. Full article

Deep learning has significantly advanced medical image analysis by enabling accurate, automated diagnosis across diverse clinical tasks such as lesion classification and disease detection. However, the practical deployment of these systems is still hindered by two major challenges: the limited availability of expert-annotated data and substantial domain shifts caused by variations in imaging devices, acquisition protocols, and patient populations. Although recent semi-supervised domain generalization (SSDG) approaches attempt to address these challenges, they often suffer from two key limitations: (i) reliance on computationally expensive uncertainty modeling techniques such as Monte Carlo dropout, and (ii) inflexible shared-head classifiers that fail to capture domain-specific variability across heterogeneous imaging styles. To overcome these limitations, we propose MultiStyle-SSDG, a unified semi-supervised domain generalization framework designed to improve model generalization in low-label scenarios. Our method introduces a multi-style ensemble pseudo-labeling strategy guided by entropy-based filtering, incorporates prototype-based conformity and semantic alignment to regularize the feature space, and employs a domain-specific multi-head classifier fused through attention-weighted prediction. Additionally, we introduce a dual-level neural-style transfer pipeline that simulates realistic domain shifts while preserving diagnostic semantics. We validated our framework on the ISIC2019 skin lesion classification benchmark using 5% and 10% labeled data. MultiStyle-SSDG consistently outperformed recent state-of-the-art methods such as FixMatch, StyleMatch, and UPLM, achieving statistically significant improvements in classification accuracy under simulated domain shifts including style, background, and corruption. Specifically, our method achieved 78.6% accuracy with 5% labeled data and 80.3% with 10% labeled data on ISIC2019, surpassing FixMatch by 4.9–5.3 percentage points and UPLM by 2.1–2.4 points. Ablation studies further confirmed the individual contributions of each component, and t-SNE visualizations illustrate enhanced intra-class compactness and cross-domain feature consistency. These results demonstrate that our style-aware, modular framework offers a robust and scalable solution for generalizable computer-aided diagnosis in real-world medical imaging settings. Full article