Search Results (2,868)

Given automotive PEMFCs’ susceptibility to thermal runaway and uneven temperature distribution under high-power-density operation, this study proposes a novel embedded pulsating heat pipe cooling system. The core innovations of this work are threefold, fundamentally distinguishing it from prior PHP cooling approaches: (1) an embedded PHP cooling plate design that integrates the heat pipe within a unified copper plate, eliminating the need for external attachment or complex bipolar plate channels and enhancing structural compactness; (2) a system-level modeling methodology that derives an effective thermal conductivity (k_eff ≈ 65,000 W·m⁻¹·K⁻¹) from a thermal resistance network for seamless integration into a full-stack CFD model, significantly simplifying the simulation of the passive PHP component; and (3) a parametric system-level optimization of the secondary active cooling loop. Numerical results demonstrate that the system achieves an exceptional maximum temperature difference (ΔT_max) of less than 1.7 K within the PEMFC stack at an optimal coolant flow rate of 0.11 m/s, far surpassing the performance of conventional liquid cooling baselines. This three-layer framework (PHP heat transfer, cooling plate conduction, liquid coolant convection) offers robust theoretical and design support for high-efficiency, passive-dominant thermal control of automotive fuel cells. Full article

The rapid advancement of communication systems has heightened the demand for efficient and robust modulation recognition. Conventional deep learning-based methods, however, often struggle in practical few-shot scenarios where acquiring sufficient labeled training data is prohibitive. To bridge this gap, this paper proposes a hybrid transfer learning (HTL) approach that synergistically combines the representation power of deep feature extraction with the flexibility and stability of traditional machine learning (ML) classifiers. The proposed method capitalizes on knowledge transferred from large-scale auxiliary datasets through pre-training, followed by few-shot adaptation using simple ML classifiers. Multiple classical ML classifiers are incorporated and evaluated within the HTL framework for few-shot modulation recognition (FSMR). Comprehensive experiments demonstrate that HTL consistently outperforms existing baseline methods in such data-scarce settings. Furthermore, a detailed analysis of several key parameters is conducted to assess their impact on performance and to inform deployment in practical environments. Notably, the results indicate that the K-nearest neighbor classifier, owing to its instance-based and non-parametric nature, delivers the most robust and generalizable performance within the HTL paradigm, offering a promising solution for reliable FSMR in real-world applications. Full article

Connected and Autonomous Electric Vehicles (CAEVs) and Uncrewed Aerial Vehicles (UAVs) are critical components of future Intelligent Transportation Systems (ITS), yet their deployment remains constrained by fragmented charging infrastructures and the lack of coordinated reservation and trip planning across static, dynamic wireless, and vehicle-to-vehicle (V2V) charging networks using magnetic resonance and laser-based power transfer. Existing solutions often struggle with misalignment sensitivity, unpredictable arrivals, and disconnected ground–aerial scheduling. This work introduces a three-layer architecture that integrates a handshake protocol for coordinated charging and billing, a misalignment correction algorithm for magnetic resonance and laser-based systems, and three scheduling strategies: Static Heuristic Charging Scheduling and Planning (SH-CSP), Dynamic Heuristic Charging Scheduling and Planning (DH-CSP), and the Safety, Scheduling, and Sustainability-Aware Feasibility-Enhanced Deep Deterministic Policy Gradient (SAFE-DDPG). SAFE-DDPG extends vanilla DDPG with feasibility-aware action filtering, prioritized replay, and adaptive exploration to enable real-time scheduling in heterogeneous and congested charging networks. Results show that SAFE-DDPG significantly improves scheduling efficiency, reducing average wait times by over 70% compared to DH-CSP and over 85% compared to SH-CSP, demonstrating its potential to support scalable and coordinated ground–aerial charging ecosystems. Full article

An efficient thermal management system (TMS) is essential for ensuring hybrid-electric aircraft (HEA) can handle the significant heat rejection required by electrified propulsion. This paper presents a system-level analysis of a compact P2PL TMS for a 1.4 MW battery generating a 70 kW heat load. A modular modeling method was used to size the key components, and then dynamic simulations were conducted under varying environmental conditions. The results indicate that a compact TMS weighing 22 kg can be developed, with a condenser heat transfer area of 26.20 m² and operating with a refrigerant mass flow rate of 0.56 kg/s while maintaining low pump power consumption at 22 W. This system can successfully regulate a battery’s temperature so that it remains below 40 °C in both standard (15 °C) and cold (−20 °C) environments. Pressure analysis confirmed the system’s flexibility and its ability to control battery temperature between 27 °C and 38 °C by adjusting the working pressure (6–8 bar). Furthermore, under hot day conditions (40 °C), battery temperature can be maintained at 47.6 °C. Even under extreme conditions (50 °C), the TMS limits the temperature to 57.45 °C, ensuring it stays within the safe operating range. Full article

Metallaphotoredox catalysis merges the powerful bond-forming abilities of transition metal catalysis with unique electron or energy transfer pathways accessible in photoexcited states, injecting new vitality into organic synthesis. However, most transition metal catalysts cannot be excited by visible light. Thus, prevalent metallaphotoredox catalytic systems require dual catalysts: a transition metal catalyst and a separate photosensitizer. This leads to inefficient electron transfer between these two low-concentration catalytic species, which often limits overall photocatalytic performance. Single-atom site catalysts (SASCs) offer a promising solution, wherein isolated and quasi-homogeneous transition metal sites are anchored on heterogeneous supports. When semiconductors are employed as the support, the photosensitive unit and transition metal catalytic site can be integrated into one system. This integration switches the electron transfer mode from intermolecular to intramolecular, thereby significantly enhancing photocatalytic efficiency. Furthermore, such heterogeneous catalysts are easier to separate and reuse. This review summarizes recent advances in the application of SASCs for photocatalytic organic synthesis, with a particular focus on elucidating structure–activity relationships of the single-atom sites. Full article

This study, based on the specifications of implantable medical devices for wireless power transfer, presents a bootstrap-comparator rectifier circuit design characterized by high voltage conversion efficiency, high power conversion efficiency, and improved reliability. The design is implemented using a 0.18 µm process to achieve superior VCE and PCE performance. The input signal is a 2 MHz, 3.3 V sine wave, producing an output voltage of 2.94 V with a maximum operating current of 5 mA. At an output load of $R_L=8\mathrm{k}\Omega$, the maximum voltage conversion efficiency (VCE) reaches 89.02%, while the maximum power conversion efficiency (PCE) is 84.73% at $R_L=500\Omega$. The temperature rise ($\Delta T$) is 0.22–$0.45{}^{\circ }\mathrm{C}$. Full article

Infrared thermal field (ITF) prediction for meter boxes is crucial for the early warning of power system faults, yet this method faces three major challenges: data sparsity, complex geometry, and resource constraints in edge computing. Existing physics-informed neural network-graph neural network (PINN-GNN) approaches suffer from redundant physics residual calculations (over 70% of flat regions contain little information) and poor model generalization (requiring retraining for new box types), making them inefficient for deployment on edge devices. This paper proposes the PhysGraphIR framework, which employs an Adaptive Residual Sampling (ARS) mechanism to dynamically identify hotspot region nodes through a physics-aware gating network, calculating physics residuals only at critical nodes to reduce computational overhead by over 80%. In this study, a ‘hotspot region’ is explicitly defined as a localized area exhibiting significant temperature elevation relative to the background—typically concentrated around electrical connection terminals or wire entrances—which is critical for identifying potential thermal faults under sparse data conditions. Additionally, it utilizes a Physics Knowledge Distillation Graph Neural Network (Physics-KD GNN) to decouple physics learning from geometric learning, transferring universal heat conduction knowledge to specific meter box geometries through a teacher–student architecture. Experimental results demonstrate that on both synthetic and real-world meter box datasets, PhysGraphIR achieves a hotspot region mean absolute error (MAE) of 11.8 °C under 60% infrared data missing conditions, representing a 22% improvement over traditional PINN-GNN. The training speed is accelerated by 3.1 times, requiring only five infrared samples to adapt to new box types. The experiments prove that this method significantly enhances prediction accuracy and computational efficiency under sparse infrared data while maintaining physical consistency, providing a feasible solution for edge intelligence in power systems. Full article

Laser Wireless Power Transmission (LWPT), as a revolutionary energy supply technology, holds broad application prospects in areas such as drone endurance, space solar energy transmission, and power supply in remote regions. The core efficiency of this technology primarily depends on the energy concentration and uniformity of the light spot at the receiving end. Through systematic simulation analysis, this paper studies the spot uniformity and energy transmission efficiency of Gaussian beams, vortex beams, and flat-topped beams under different atmospheric conditions (turbulence intensity, visibility) and transmission distances. By quantitatively analyzing key indicators such as light spot non-uniformity and power density within the bucket, the advantages and disadvantages of the three beam types are comprehensively evaluated. The results indicate that the flat-topped beam is the optimal choice for short-distance laser energy transfer under favorable atmospheric conditions, while the vortex beam exhibits the best overall performance and robustness in medium and strong turbulence transmission environments. This study provides a theoretical basis for beam selection in different application scenarios. Full article

Driven by global initiatives to mitigate climate change, the offshore wind power industry is experiencing rapid growth. Personnel transfer between service operation vessels (SOVs) and offshore wind turbines under complex sea conditions remains a critical factor governing the safety and efficiency of operation and maintenance (O&M) activities. This study establishes a fully coupled dynamic response and control simulation framework for an SOV equipped with an active motion-compensated gangway. A numerical model of the SOV is first developed using potential flow theory and frequency-domain multi-body hydrodynamics to predict realistic vessel motions, which serve as excitation inputs to a co-simulation environment (MATLAB/Simulink coupled with MSC Adams) representing the Stewart platform-based gangway. To address system nonlinearity and coupling, a composite control strategy integrating velocity and dynamic feedforward with three-loop PID feedback is proposed. Simulation results demonstrate that the composite strategy achieves an average disturbance isolation degree of 21.81 dB, significantly outperforming traditional PID control. Validation is conducted using a ship motion simulation platform and a combined wind–wave basin with a 1:10 scaled prototype. Experimental results confirm high compensation accuracy, with heave variation maintained within 1.6 cm and a relative error between simulation and experiment of approximately 18.2%. These findings demonstrate the framework’s capability to ensure safe personnel transfer by effectively isolating complex vessel motions and validate the reliability of the coupled dynamic model for offshore operational forecasting. Full article

Microwave wireless power transfer (MWPT) technology has the advantages of long distance and high transmission efficiency; therefore, MWPT has many applications in aerospace, space solar power stations (SSPSs), and so on. The receiving and fixing subsystem is the core component for gathering and converting power and it is the main part of the system. If this step is both efficient and possible, the whole system will also be efficient and its success possible. This paper mainly introduces a systematic review of the key technologies, research status, and development trends of the receiving-end part in MWPT. High-performance rectifying devices are analyzed in detail, with the use of GaN Schottky barrier diodes (GaN SBDs), in addition to rectification circuits that have good rectification and impedance matching. Additionally, it compares the advantages and disadvantages of three power synthesis architectures, including RF synthesis, DC synthesis, and hybrid subarray synthesis, and proposes a strategy for optimizing power distribution through intelligent subarray partitioning. Finally, this paper looks at future development trends in receiving-end technology, including miniaturized monolithic microwave integrated circuits (MMICs) and efficient broadband reconfigurable rectification. The research presented herein offers a systematic technical reference and theoretical foundation for enhancing the performance of the receiving ends in microwave wireless power transfer systems. Full article

This study demonstrates a sustainable, integrated pathway for valorizing carrot processing by-products through solvent-free lycopene recovery. The approach combines optimized infrared dehydration with ultrasound-assisted extraction using edible oils. Drying kinetics were modeled at multiple temperatures, with the Midilli model providing the best fit (R² > 0.99), enabling accurate prediction of moisture content removal while preserving bioactive compounds. Optimization via Box–Behnken design identified efficient extraction conditions (49.7–60 °C, 10 mL/g, 60 min), achieving lycopene equivalent (LE) yields of 3.07 to 5.00 mg/kg oil. Sunflower and blended oils showed comparable performance under maximum sonication power (240 W), with strong agreement between predicted and experimental yields. The process generated two valuable outputs: a functional lycopene-enriched oil and an exhausted carrot powder co-product, the latter retaining its crude fiber content despite other compositional changes. This research presents a scalable, green methodology that aligns with circular economy principles, transforming agro-industrial waste into functional food ingredients without organic solvents. Thus, the developed approach establishes a transferable model for the sustainable valorization of carotenoid-rich residues, contributing directly to greener food production systems. By providing a practical technological framework to convert waste into wealth, this work supports the fundamental transition toward a circular bioeconomy. Full article

Modern processes to produce rare-earth elements, strategic metals, and nuclear fuel reprocessing require highly efficient liquid–liquid extraction in systems characterized by high viscosity, elevated interfacial tension, and small density differences. Traditional gravity-driven extractors exhibit low performance under these conditions, whereas centrifugal extractors enable rapid mass transfer and nearly complete phase separation. Differential-contact annular centrifugal contactors offer the highest flexibility and efficiency, but their optimization is limited by the lack of experimental data on the hydrodynamics of liquid flow through perforated nozzles in a rotating field. This limitation hinders the development of accurate computational fluid dynamics (CFD) models (e.g., ANSYS Fluent), reliable equipment scale-up, and the design of optimized contactor configurations. The present study addresses this gap by experimentally determining the flow velocity of liquids through nozzles of various geometries across a wide range of centrifugal accelerations. From these data, a universal power-law correlation was derived, linking the flow rate to rotor speed, nozzle geometry, and the physicochemical properties of the phases. The proposed correlation provides a robust experimental basis for numerical model validation, computational design, and optimization of next-generation differential-contact centrifugal extractors. Full article

This work presents the fabrication and characterization of a bow-tie antenna integrated uni-traveling carrier photodiode (UTC-PD) on a silicon carbide (SiC) substrate for efficient terahertz (THz) wave generation. The proposed device exploits the superior thermal conductivity and mechanical robustness of SiC to overcome the self-heating limitations associated with conventional indium phosphide (InP)-based photodiodes. An epitaxial layer transfer technique was utilized to bond InP/InGaAs UTC-PD structures onto SiC. The study systematically examines the influence of critical geometric parameters, specifically the mesa diameter and length between the antenna arms, on the emitted THz intensity in the 300 GHz frequency band. Experimental results show that the THz radiation efficiency is primarily governed by the mesa diameter, reflecting the trade-off between light absorption, device capacitance, and bandwidth, while the length between the antenna arms exhibits only a weak influence within the investigated parameter range. The fabricated device demonstrates strong linearity between photocurrent and THz output power up to 7.5 mA, after which saturation occurs due to space-charge effects. This work provides crucial insights for optimizing SiC-based bow-tie antenna integrated UTC-PD devices to realize robust, high-power THz sources vital for future high-data-rate wireless communication systems such as beyond 5G and 6G networks. Full article

Wireless Power Transfer (WPT) has become a pivotal technology, enabling the battery-free operation of Internet of Things (IoT) and biomedical devices while supporting environmental sustainability. This review provides a comprehensive analysis of microstrip patch antennas (MPAs) operating at the 5.8 GHz Industrial, Scientific, and Medical (ISM) band, emphasizing their advantages over the more commonly used 2.4 GHz band. A detailed and systematic classification framework for MPA architectures is introduced, covering single-element, multi-band, ultra-wideband, array, MIMO, wearable, and rectenna systems. The review examines advanced optimization methodologies, including Defected Ground Structures (DGS), Electromagnetic Bandgap (EBG) structures, Metamaterials (MTM), Machine Learning (ML), and nanomaterials, each contributing to improvements in gain, bandwidth, efficiency, and device miniaturization. Unlike previous surveys, this work offers a performance-benchmarked classification specifically for 5.8 GHz MPAs and provides a quantitative assessment of key trade-offs, such as efficiency versus substrate cost. The review also advocates for a shift toward Power Conversion Efficiency (PCE)-centric co-design strategies. The analysis identifies critical research gaps, particularly the ongoing disparity between simulated and experimental performance. The review concludes by recommending multi-objective optimization, integrated antenna-rectifier co-design to maximize PCE, and the use of advanced materials and computational intelligence to advance next-generation, high-efficiency 5.8 GHz WPT systems. Full article

This study presents an experimental 3E (energy–exergy–environmental) assessment of a PLC-controlled solar air heater (SAH) equipped with adjustable internal baffles. Unlike conventional passive systems, the proposed design enables active airflow regulation to maintain stable outlet temperatures of 54 °C and 60 °C, achieving rapid stabilization within 3–10 s under outdoor conditions. Experimental results show that increasing the baffle inclination significantly enhances convective heat transfer and thermal efficiency, while the friction factor remains primarily governed by the Reynolds number and exhibits minimal sensitivity to baffle angle. Exergy efficiency values remain relatively low (1.24–2.69%), and the sustainability index stays close to unity, reflecting the inherent thermodynamic limitations of low-temperature solar air heaters rather than deficiencies in system design. A regression-based airflow velocity model is developed to support fan-speed optimization and to clarify the trade-off between thermal enhancement and auxiliary power demand. Long-term projections based on regional solar data indicate that the proposed SAH can deliver approximately 20–22 MWh of useful heat and mitigate nearly 9 tons of CO₂ emissions over a 20-year operational lifetime. Overall, the results demonstrate that PLC-assisted dynamic baffle control provides a flexible and effective approach for improving the performance and operational stability of solar air heaters for low-temperature drying applications. Full article