Search Results (143)

To obtain ultrahigh strength Cu alloy strip for board-to-board connectors, a CuNiSiMgMn multi-element high-solute alloy was designed, and high-temperature short-time solid solution was utilized to optimize the properties of this alloy. The evolution in microstructure and properties of the cold-rolled CuNiSiMgMn alloy strip during high-temperature short-time solid solution, aging, and further cold-rolling are investigated. The results reveal that there are high-density Ni_xSi precipitates and deformation defects in the original cold-rolled CuNiSiMgMn alloy strip. During a solid solution at 1000 °C, recrystallization primarily occurs between 15 and 30 s, while precipitate decomposition starts at a solid solution time of ~30 s and is almost complete 10 s later. With further increase in the solid solution time, the grain size of the alloy grows rapidly, but the residual precipitate particles exhibit little change. Upon aging at 500 °C for 2 h and a further 80% cold-rolling, nano-sized precipitates are formed, yielding high-strength alloy strips. The 80% cold-rolling increases the microhardness by 12% and decreases the electrical conductivity by 3% IACS. The strip solid solution-treated for 35 s exhibits the maximum strength, with a tensile strength of >950 MPa and a conductivity of >30% IACS. Further extension of the solid solution time decreases both the tensile strength and elongation. This work clarifies the critical time of recovery, recrystallization, and precipitate decomposition of the CuNiSiMgMn alloy during high-temperature solid solution and provides guidance for industrial production. Full article

The accelerating adoption of electric vehicles (EVs) is driving the demand for next-generation wide-bandgap (WBG) power devices that can deliver high efficiency, high power density, and robust operation under stringent electrical and thermal stress. Gallium nitride (GaN) high-electron-mobility transistors (HEMTs) have emerged as a leading WBG technology due to their high breakdown voltage, ultrafast switching capability, and low conduction and switching losses relative to silicon devices, enabling high-performance EV power converters such as on-board chargers, DC-DC converters, and traction inverters. This review provides a comprehensive device-level assessment of GaN HEMTs, emphasizing advanced device architectures, state-of-the-art discrete transistors, and their implications for high-frequency, high-efficiency power conversion. Critical performance and reliability challenges, including current collapse, self-heating, and gate degradation, are analyzed in the context of their physical mechanisms and operational behavior under realistic conditions such as elevated junction temperatures, high switching frequencies, and dynamic load profiles. Furthermore, emerging opportunities in ultra-wide-bandgap semiconductor technologies beyond GaN are discussed, providing insights to guide the design, optimization, and robust integration of WBG devices into next-generation EV power electronic systems. Full article

This research investigates novel polymeric composite materials made from recycled polyolefin and waste plant biomass (poplar seeds and vegetable peels), which have potential applications in the relatively unexplored field of electrical insulation. For composites made from poplar seeds with low density polyethylene matrix, the structure appears more uniform, even with increased biomass content, in contrast to those utilizing high density polyethylene matrix, which displays notable heterogeneous areas where the polymer appears separated from the fibrous network at higher biomass levels. Concerning the composites of vegetable peels with high density polyethylene matrix, the fragments of vegetable peels are clearly recognizable, and their bond to the polymer matrix appears weaker. When incorporating vegetable peels into the polypropylene matrix, it results in a better distribution of the vegetable peel fragments within the polymer matrix, as well as enhanced structural homogeneity. Overall, the incorporation of biomass reduces the Shore hardness measurement for every polymer matrix. Regarding tear resistance, the inclusion of biomass reduces the values only for low density polyethylene with poplar seeds. For both high density polyethylene and polypropylene, regardless of the biomass type, the property seems to enhance marginally with the addition of biomass. The primary advantage of utilizing these composites is that their water absorption rate is at least twice as low as that of transformer board, while still offering a similar capacity for absorbing transformer oil. All composite types exceeded the minimum required threshold of 70 °C for service exposure, and adhered to insulation class A, similar to cellulose-based insulations. The addition of cellulose to polyolefin composites appears to slightly improve their breakdown strength. The conductivity for this type of composite is at least three times lower than that of cellulose insulation materials, rendering them beneficial for applications in electrical engineering as potential substitutes for cellulose-based materials in multiple electrical insulation uses, e.g., for insulating low voltage electrical machines, as well as serving as a substitute for pressboard in transformers. Additionally, their thermoplastic properties offer enhanced processing versatility, opening up new opportunities for electrical engineering technology, especially with regard to electrical insulation recyclability in the context of a circular economy. Full article

This research demonstrates the principle and optimization methodology to create economic and miniaturized high-resolution micro-moisture sensors. The interdigitated fringe electric field-based moisture measurement principle is firstly investigated to sketch the key parameters of printed circuit board (PCB)-based sensors for further performance optimization. Then, a comprehensive study is conducted to analyze parameter variations with conclusions of suggested design rules to achieve higher measurement sensitivity. Two prototypes are designed and manufactured to validate the proposed theoretical contributions. Water droplets are employed to control the ambient relative humidity, which is adopted as the actual moisture variable in this work. A double-correlated sampling circuit is used for capacitance sensing. Both of them demonstrate a linearity of 1% and sensitivity of 0.1 pF/mg levels, but prototype 2 gains a better batch consistency, which is beneficial for commercialization. Further data analysis suggests that the equivalent input–output sensitivity reaches a level of 1.2403 pF/%RH (relative humidity), which is significantly higher than other types of published interdigitated fringe electric field-type moisture sensors. The optimized prototypes also show advantages of miniaturized size, low cost and high consistency, which can potentially impact the industry applications. Full article

The reliability of biomedical devices is closely linked to the quality and long-term stability of the electronic circuits that support their operation. Printed circuit boards (PCBs), in particular, can be affected by manufacturing imperfections, thermal stress and progressive ageing, which may lead to failures during the device life cycle. In this study, we present the design and simulation-based validation of an embedded acquisition circuit aimed at monitoring PCB electrical integrity in a non-invasive and remote manner. The presented solution is based on Hall-effect current sensing combined with a 16-bit analog-to-digital conversion stage and a digital communication interface managed by a Raspberry Pi. This configuration allows the system not only to acquire integrity-related electrical signals but also to process them locally and transmit them wirelessly for supervision purposes. A lightweight artificial intelligence model is implemented directly on the embedded platform to analyse the acquired signals and to classify different PCB operating conditions in real time. Simulation results show that the system is able to identify small current variations caused by micro-discontinuities and abnormal conductive paths. The classification accuracy exceeds 97% for PCB integrity states, confirming the suitability of the approach for remote monitoring, predictive maintenance and safety support in electromedical devices. Full article

This study systematically investigates the structural optimization and control strategies of a plasma power supply-based rotating electrical machine. Firstly, stress simulation analysis was conducted on both conventional and optimized motor structures using ANSYS 2025 R1 software. The results demonstrate the maximum stress at the motor bearings decreased from 1.295 MPa to 0.865 MPa after optimization, representing a 33.2% reduction. Secondly, dynamic balance simulation performed with Adams 2024 software revealed that the centroid offset range of the optimized motor was reduced from ±0.05 mm to ±0.0175 mm, achieving a 65% improvement. Furthermore, a motor driver board supporting SVPWM and FOC algorithm was designed and implemented, featuring wide voltage input, multiple output channels, and comprehensive protection functions. Experimental verification confirmed that the developed control system could generate ideal three-phase saddle wave and sinusoidal current waveforms, ensuring smooth motor operation. The system demonstrated excellent dyne pen test results on plasma-sprayed acrylic plates, effectively validating the feasibility of both structural optimization and control strategies. The research outcomes provide theoretical foundations and technical support for high-performance motor design in demanding applications such as plasma spraying. Full article

Waste electrical and electronic equipment (WEEE) is a rapidly growing waste stream rich in precious metals, with gold in particular being concentrated in printed circuit boards and other high-value components. Historically, industrial recycling has relied on pyrometallurgy and non-selective hydrometallurgical leaching. These recovery routes have major drawbacks, including high energy demand, corrosion, the use of toxic reagents, and the complexity of pregnant leach solutions, which complicate downstream gold recovery. This review aims to synthesize recent advances in selective gold recovery from WEEE using a speciation-driven approach. Mechanical pretreatment and physical beneficiation methods are critically assessed as processes for concentrating gold and reducing the amount of material sent to downstream hydrometallurgical leaching. Different lixiviants, from conventional cyanide to halide-based, as well as greener chemistries such as thiosulfate and thiourea, are assessed for gold dissolution from the WEEE stream. Assessment of different extraction methods, including sorbents, ion exchange resins, solvent/ionic liquid, direct reduction/precipitation, and electrochemical recovery, is conducted. The review concludes with guidelines for potential process integration and highlights the need for scalable, reusable lixiviants and sorbent materials validated under realistic multi-metal conditions in real WEEE leachate. Full article

The escalating volume of waste electrical and electronic equipment (WEEE) poses a significant global environmental challenge. The disassembly of printed circuit boards (PCBs), a critical step for resource recovery, remains inefficient due to limitations in the adaptability and dexterity of existing automated systems. This paper proposes an intelligent disassembly system for PCB components that integrates a multimodal large language model (MLLM) with a multi-agent framework. The MLLM serves as the system’s cognitive core, enabling high-level visual-language understanding and task planning by converting images into semantic descriptions and generating disassembly strategies. A state-of-the-art object detection algorithm (YOLOv13) is incorporated to provide fine-grained component localization. This high-level intelligence is seamlessly connected to low-level execution through a multi-agent framework that orchestrates collaborative dual robotic arms. One arm controls a heater for precise solder melting, while the other performs fine “probing-grasping” actions guided by real-time force feedback. Experiments were conducted on 30 decommissioned smart electricity meter PCBs, evaluating the system on recognition rate, capture rate, melting rate, and time consumption for seven component types. Results demonstrate that the system achieved a 100% melting rate across all components and high recognition rates (90–100%), validating its strengths in perception and thermal control. However, the capture rate varied significantly, highlighting the grasping of small, low-profile components as the primary bottleneck. This research presents a significant step towards autonomous, non-destructive e-waste recycling by effectively combining high-level cognitive intelligence with low-level robotic control, while also clearly identifying key areas for future improvement. Full article

This paper presents the reconstruction of signal paths acquired from a power electronics system for energy conversion and management. This reconstruction is performed using the Kalman filter (KF) for monitoring photovoltaic (PV) systems enabled for Internet of Things (IoT) systems. This proposal is motivated by the fact that the global energy transition towards renewable sources makes PV systems a crucial alternative. To guarantee the efficiency and stability of these systems, monitoring critical electrical parameters using IoT technology is essential. However, the measurements acquired are frequently corrupted by stochastic noise, which obscures the true behavior of the system and limits its accurate characterization. Based on this problem, the main objective of this work is explicitly defined as evaluating the effectiveness of the KF as a power-path reconstruction method capable of recovering accurate electrical trajectories from noisy measurements in IoT-monitored photovoltaic networks. To achieve this goal, the system is modeled as a discrete-time stochastic process and the KF is implemented as a real-time estimator of power flow behavior. The experiment was conducted using real-world generation and consumption data from a proprietary two-layer IoT platform: an Edge Layer (acquisition with ESP8266 and PZEM-004T-100A sensors) and a Cloud Layer (visualization on Things-Board). To validate the results, quantitative metrics including the mean squared error (MSE), statistical moments, and probability distributions were computed. The MSE values were found to be nearly zero across all reconstructed power-paths. The statistical moments exhibited near-perfect agreement with those of the actual power signals, approaching 100% correspondence. Additionally, the probability distributions were compared visually and assessed statistically using the Kolmogorov–Smirnov (KS) test. The resulting KS values were very low, confirming the high accuracy of the reconstruction for all power-paths. The proposed research concluded that the KF successfully reconstructed the power trajectories, demonstrating high agreement with the measured steady-state behavior. This study thus confirms that integrating Kalman filtering with IoT monitoring delivers a practically viable and statistically accurate method for power trajectory reconstruction, which is fundamental for enhancing the observability and reliability of photovoltaic energy systems. Full article

This study conducts a numerical investigation of the geometry of the oscillating water column (OWC) wave energy converter under realistic irregular wave conditions found off the coast of Rio Grande, southern Brazil. Two OWC models were compared: the conventional design and the L-shaped configuration (L-OWC). The OWC structure consists of a hydropneumatic chamber and an air duct, where a turbine is coupled to an electric generator. Additionally, in the L-shaped chamber configuration, a water intake duct is considered. The constructal design method was employed for the geometric evaluation of the devices. For the L-OWC, the influence of the height-to-length ratio of the water intake duct on the obtained hydropneumatic power available was analyzed. In parallel, for the conventional OWC, the free-board submergence was investigated. Subsequently, the optimal geometry for each OWC model was selected to study the height-to-length ratio of the hydropneumatic chamber. Numerical simulations were performed using ANSYS Fluent software. Thus, the performance of the converters was improved by approximately 35.76 times for the L-OWC and 3.78 times for the conventional OWC. However, it is noteworthy that the optimal configuration of the conventional OWC achieved a performance 2.62 times higher than the optimal L-OWC geometry. Full article

This paper presents a comprehensive methodology to forecast the daily energy demand associated with recharging private electric vehicles in urban areas. The approach is based on plausible scenarios regarding the penetration of battery-powered vehicles and the availability of charging infrastructure. Accurate space and time forecasting of charging activities and power requirements is a critical issue in supporting the transition from conventional to battery-powered vehicles for urban mobility. This technological shift represents a key milestone toward achieving the zero-emissions target set by the European Green Deal for 2050. The methodology leverages Floating Car Data (FCD) samples. The widespread use of On-Board Units (OBUs) in private vehicles for insurance purposes ensures the methodology’s applicability across diverse geographical contexts. In addition to FCD samples, the estimation of charging demand for private electric vehicles is informed by a large-scale, detailed survey conducted by ENEA in Italy in 2023. Funded by the Ministry of Environment and Energy Security as part of the National Research on the Electric System, the survey explored individual charging behaviors during daily urban trips and was designed to calibrate a discrete choice model. To date, the methodology has been applied to the Metropolitan Area of Rome, demonstrating robustness and reliability in its results on two different scenarios of analysis. Each demand/supply scenario has been evaluated in terms of the hourly distribution of peak charging power demand, at the level of individual urban zones or across broader areas. Results highlight the role of the different components of power demand (at home or at other destinations) in both scenarios. Charging at intermediate destinations exhibits a dual peak pattern—one in the early morning hours and another in the afternoon—whereas home-based charging shows a pronounced peak during evening return hours and a secondary peak in the early afternoon, corresponding to a decline in charging activity at other destinations. Power distributions, as expected, sensibly differ from one scenario to the other, conditional to different assumptions of private and public recharge availability and characteristics. Full article

Electromagnetic compatibility is the capability of electrical and electronic equipment to function properly around devices radiating electromagnetic energy, without mutual disturbance. Hospital environments contain numerous devices operating simultaneously and sharing resources. Undetected electromagnetic interference can cause medical devices’ malfunctions, exposing patients and staff. Traditional monitoring is time-consuming and relies on expert interpretation. An Internet of Things-enabled embedded system architecture for remote and real-time monitoring of electromagnetic fields from medical devices is proposed. It integrates frequency probes, a Raspberry Pi 4, and a communication module. A three-month study conducted at Muhima District Hospital, Kigali, Rwanda, demonstrated the system’s effectiveness in monitoring electromagnetic field levels and cloud transmission. The signals were benchmarked against International Electrotechnical Commission and Rwanda Standards Board standards. Alerts are triggered when thresholds are exceeded, with results plotted on website and mobile interfaces. Emissions were highest at noon when the equipment was most active and lower after 1:30 PM, indicating reduced activity. The sample recorded statistics of electric fields include mean (1.0028), minimum (0.7228), and maximum (1.3515). Among the five filters evaluated, the Savitzky–Golay performed better, with MSE (0.235) and SNR (9.308). A 412 ms average latency and 24 h operation was achieved, offering a portable solution for hospital safety and equipment optimization. Full article

Discrete Silicon Carbide Metal-Oxide-Semiconductor Field-Effect Transistors (SiC MOSFETs) are characterized by their lower parasitic parameters and single-chip design, enabling them to achieve even faster switching speeds. However, the rapid rate of change in voltage (dv/dt) and current (di/dt) can lead to overshoot and oscillation in both voltage and current, ultimately limiting the performance of high-frequency operations. To address this issue, this paper presents a high-switching-frequency motor controller that utilizes discrete SiC MOSFETs. To achieve a high switching frequency for the controller while minimizing current oscillation and voltage overshoot, a novel electronic system architecture is proposed. Additionally, a passive driving circuit is designed to suppress gate oscillation without the need for additional control circuits. A new printed circuit board (PCB) laminate stack featuring low parasitic inductance, high current conduction capacity, and efficient heat dissipation is also developed using advanced wiring technology and a specialized heat dissipation structure. Compared to traditional methods, the proposed circuit and bus design features a simpler structure, a higher power density, and achieves a 13% reduction in current overshoot, along with a 15.7% decrease in switching loss. The silicon carbide (SiC) controller developed from this research has successfully undergone double-pulse and power testing. The results indicate that the designed controller can operate reliably over extended periods at a switching frequency of 50 kHz, achieving a maximum efficiency of 98.2% and a power density of 9 kW/kg (10 kW/L). The switching frequency and quality density achieved by the controller have not been observed in previous studies. This controller is suitable for use in the development of new energy electrical systems. Full article

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting intuitive user interaction. Results indicate that the prosthesis successfully mimics natural finger flexion and adapts effectively to a variety of grasping tasks with minimal effort. This study was conducted in accordance with ethical standards and approved by the Institutional Review Board (IRB), Project No. 670161, titled “Biologically-Inspired Synthetic Finger: Design, Fabrication, and Application.” The findings suggest that the device offers a viable and practical solution for individuals with partial hand loss, particularly in settings where electrically powered systems are unsuitable or inaccessible. Full article

Global resource consumption continues to grow each year, exerting increasing pressure on their availability. This trend could lead to a shortage of raw materials in the coming years. Aware of the risks associated with this situation, the European Union has implemented policies and strategies aimed at diversifying its supply sources, including waste recycling. In this context, the present study was conducted with the objective of developing innovative processes to concentrate valuable metals present in the non-recovered fractions of waste electrical and electronic equipment (WEEE). Three types of samples were studied: washing table residues (WTRs), printed circuit boards (PCBs), and powders from cathode-ray tube screens (CRT powders). Several separation techniques, based on the physical properties of the elements, were implemented, including electrostatic separation, magnetic separation, and density and gravity-based separations. The results obtained are promising. For WTRs and PCBs, the recovery rates of targeted metals (Cu, Al, Pb, Zn, Sn) reached approximately 91% and 80%, respectively. In addition to these metals, other valuable metals, present in significant quantities, deserve further exploration. Regarding CRT powders, the performances are also encouraging, with recovery rates of 54.7% for zinc, 57.1% for yttrium, and approximately 71% for europium. Although these results are satisfactory, optimizations are possible to maximize the recovery of these critical elements. The techniques implemented have demonstrated their effectiveness in concentrating target metals in the treated fractions. These results confirm that recycling constitutes a viable alternative to address resource shortages and secure part of the supplies needed for the European Union’s industry. Full article