Search Results (10,793)

This article presents studies of surface layers produced by electro-spark deposition (ESD) on cast iron using a W-Ni-Co sintered electrode. To minimize the number of required experiments, a two-factor, five-level Hartley experimental design was chosen. The assessment involved observing the effect of voltage and capacitor capacity during the ESD process (on layer thickness and wear of the sample and counter-sample under technically dry friction conditions). Microscopic and tomographic observations were performed to analyze the thickness and structure of the layers. Image analysis methods were employed to examine the cross-section of the layers. ESD diffusion analyses were performed on the produced layer. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX) were performed to characterize the microstructure and composition of the coating. In addition, in order to evaluate the performance properties of tungsten coatings, the tribological tests were also conducted on a TRB³ Ball-on-Disc testing device. Hardness tests confirm an increase in the hardness of cast iron with a tungsten layer by over 400 µHV. The tests showed that higher voltages during the ESD process result in thicker layers and reduced wear of the sample with a tungsten layer at the expense of increased wear of the counter-sample (ball). Full article

This research is based on the acoustic package design of new energy vehicles, investigating the application of the hybrid Finite Element–Statistical Energy Analysis (FE-SEA) model in predicting the high-frequency dynamic response of automotive structures, with a focus on the modeling and correction methods for hybrid point connections. New energy vehicles face unique acoustic challenges due to the special nature of their power systems and operating conditions, such as high-frequency noise from electric motors and electronic devices, wind noise, and road noise at low speeds, which directly affect the vehicle’s ride comfort. Therefore, optimizing the acoustic package design of new energy vehicles to reduce in-cabin noise and improve acoustic quality is an important issue in automotive engineering. In this context, this study proposes an improved point connection correction factor by optimizing the division range of the decision circle. The factor corrects the dynamic stiffness of point connections based on wave characteristics, aiming to improve the analysis accuracy of the hybrid FE-SEA model and enhance its ability to model boundary effects. Simulation results show that the proposed method can effectively improve the model’s analysis accuracy, reduce the degrees of freedom in analysis, and increase efficiency, providing important theoretical support and reference for the acoustic package design and NVH performance optimization of new energy vehicles. Full article

Voltage supraharmonics present in the electrical grid can trigger chain reactions in grid-connected household and industrial power supplies equipped with Power Factor Correction (PFC). A single source of voltage supraharmonics may significantly increase the current in switching devices with PFC, leading to higher-amplitude disturbances throughout the electrical network. When addressing issues in a real low-voltage (LV) grid, it was observed that activation of a single device emitting supraharmonics caused oscillating currents across all feeders connected to the transformer’s busbars, matching the frequency of the supraharmonic source. To investigate this phenomenon further, the grid voltage containing supraharmonics was replicated in a controlled laboratory environment and used to supply various power electronic devices. The laboratory results closely mirrored those observed in the field. Supraharmonics present in the supply voltage caused current oscillations in the power electronic devices at the same frequency. Moreover, the amplitude of the observed current oscillations increased with the amplitude of the injected supply voltage supraharmonics. In some cases, the root mean square (RMS) value of the current drawn by the power electronic devices doubled, indicating a substantial impact on device behaviour and potential implications for grid stability and energy efficiency. Full article

We explore a plasmonic interface for perovskite solar cells (PSCs) by integrating inkjet-printed TiO₂-AuNP microdot arrays (MDA) into the electron transport layer. This systematic study examines how the TiO₂ blocking layer (BL) surface conditioning, AuNP layer positioning, and nanoparticle loading collectively influence device performance. Pre-annealing the BL increases its hydrophobicity, yielding smaller and denser AuNP microdots with an enhanced localized surface plasmon resonance (LSPR). Positioning the AuNP MDA at the BL/perovskite interface (above the BL) maximizes near-field plasmonic coupling to the absorber, resulting in higher photocurrent and power conversion devices; these trends are corroborated by finite-difference time-domain (FDTD) simulations. Moreover, these devices demonstrate better stability over time compared to those with AuNPs at the transparent electrode (under BL). Although higher AuNP concentrations improve dispersion stability, preserve MAPI crystallinity, and yield more uniform nanoparticle sizes, device measurements showed no performance gains. After annealing, the samples with the Au content of 23 wt% relative to TiO₂ achieved optimal PSC efficiency by balancing plasmonic enhancement and charge transport without the increased resistance and recombination losses seen at higher loadings. Importantly, X-ray diffraction (XRD) confirms that introducing the TiO₂-AuNP MDA at the interface does not disrupt the perovskite’s crystal structure, underscoring the structural compatibility of this plasmonic enhancement. Overall, our findings highlight a scalable strategy to boost PSC efficiency via engineered light-matter interactions at the nanoscale without compromising the perovskite’s structural integrity. Full article

To maintain product reliability and stabilize performance, it is essential to prioritize the identification and resolution of latent defects. Advanced products such as high-precision electronic devices and semiconductors are susceptible to performance degradation over time due to environmental factors and electrical stress. However, conventional performance testing methods typically evaluate products based solely on predefined acceptable ranges, making it difficult to predict long-term degradation, even for products that pass initial testing. In particular, products exhibiting borderline values close to the threshold during initial inspections are at a higher risk of exceeding permissible limits as time progresses. Therefore, to ensure long-term product stability and quality, a novel approach is required that enables the early prediction of potential defects based on test data. In this context, the present study proposes a machine learning-based framework for predicting latent defects in products that are initially classified as normal. Specifically, we introduce the Sigma Deviation Count Labeling (SDCL) method, which utilizes a Gaussian distribution-based approach. This method involves preprocessing the dataset consisting of initially passed test samples by removing redundant features and handling missing values, thereby constructing a more robust input for defect prediction models. Subsequently, outlier counting and labeling are performed based on statistical thresholds defined by 2σ and 3σ, which represent potential anomalies outside the critical boundaries. This process enables the identification of statistically significant outliers, which are then used for training machine learning models. The experiments were conducted using two distinct datasets. Although both datasets share fundamental information such as time, user data, and temperature, they differ in the specific characteristics of the test parameters. By utilizing these two distinct test datasets, the proposed method aims to validate its general applicability as a Predictive Anomaly Testing (PAT) approach. Experimental results demonstrate that most models achieved high accuracy and geometric mean (GM) at the 3σ level, with maximum values of 1.0 for both metrics. Among the tested models, the Support Vector Machine (SVM) exhibited the most stable classification performance. Moreover, the consistency of results across different models further supports the robustness of the proposed method. These findings suggest that the SDCL-based PAT approach is not only stable but also highly adaptable across various datasets and testing environments. Ultimately, the proposed framework offers a promising solution for enhancing product quality and reliability by enabling the early detection and prevention of latent defects. Full article

Cu₂S has wide-ranging applications in the energy field, particularly as electrode materials and components of energy storage devices. However, the migration of copper ions is prone to component segregation and copper precipitation, impairing long-term thermal stability and service performance. Ce₂S₃ not only possesses the unique 4f electron layer structure of Ce but also has high thermal stability and chemical inertness. Here, we report for the first time that the thermal stability and mechanical properties of Cu₂S can be significantly enhanced by introducing the dispersed phase Ce₂S₃. Thermogravimetry—differential scanning calorimetry (TG-DSC) results show that the addition of 6 wt% Ce₂S₃ improves the thermal stability of Cu₂S sintered at 400 °C. X-ray diffraction (XRD) results indicate that the crystal structure of Cu₂S gradually transforms to tetragonal Cu_1.96S and orthorhombic Cu_1.8S phase at 400 °C with the increase of Ce₂S₃ addition. Scanning electron microscopy (SEM) results show that the particle size gradually decreased with the increase of Ce₂S₃ amount, indicating that the Ce₂S₃ addition increased the reactivity. The Ce content in Cu₂S increased gradually with the increase of Ce₂S₃ amount at 400–600 °C. The 7 wt% Ce₂S₃-Cu₂S exhibits paramagnetic behavior with a saturation magnetization of 1.2 µ_B/Ce. UV-Vis analysis indicates that the addition of Ce₂S₃ can reduce the optical energy gap and enrich the band structure of Cu₂S. With increasing addition of Ce₂S₃ and rising sintering temperature, the density of Ce₂S₃-Cu₂S gradually increases, and the hardness of Ce₂S₃-Cu₂S increases by 52.5% at 400 °C and by 34.2% at 600 °C. The friction test results show that an appropriate addition amount of Ce₂S₃ can increase the friction coefficients of Cu₂S. Ce₂S₃ modification offers a novel strategy to simultaneously enhance the structural and service stability of Cu₂S by regulating Cu ion diffusion and suppressing compositional fluctuations. Full article

In this study, high-conductivity W-doped Ga₂O₃ thin films were successfully fabricated by directly depositing a composition of Ga₂O₃ with 10.7 at% WO₃ (W:Ga = 12:100) using electron beam evaporation. The resulting thin films were found to be amorphous. Due to the ohmic contact behavior observed between the W-doped Ga₂O₃ film and platinum (Pt), Pt was used as the contact electrode. Current-voltage (J-V) measurements of the W-doped Ga₂O₃ thin films demonstrated that the samples exhibited significant current density even without any post-deposition annealing treatment. To further validate the excellent charge transport characteristics, Hall effect measurements were conducted. Compared to undoped Ga₂O₃ thin films, which showed non-conductive characteristics, the W-doped thin films showed an increased carrier concentration and enhanced electron mobility, along with a substantial decrease in resistivity. The measured Hall coefficient of the W-doped Ga₂O₃ thin films was negative, indicating that these thin films were n-type semiconductors. Energy-Dispersive X-ray Spectroscopy was employed to verify the elemental ratios of Ga, O, and W in the W-doped Ga₂O₃ thin films, while X-ray photoelectron spectroscopy analysis further confirmed these ratios and demonstrated their variation with the depth of the deposited thin films. Furthermore, the W-doped Ga₂O₃ thin films were deposited onto both p-type and heavily doped p⁺-type silicon (Si) substrates to fabricate heterojunction diodes. All resulting devices exhibited good rectifying behavior, highlighting the promising potential of W-doped Ga₂O₃ thin films for use in rectifying electronic components. Full article

A radiation-hardened RCC (Ring Choke Converter) isolated power supply design is proposed, which provides an innovative solution to the challenge of providing stable power to the PWM controller in DC-DC converters under nuclear radiation environments. By optimizing circuit architecture and component selection, and incorporating transformer isolation and dynamic parameter compensation technology, the RCC maintains an 8.9 V output voltage after exposure to neutron irradiation of 3 × 10¹³ n/cm², significantly outperforming conventional designs with a failure threshold of 1 × 10¹³ n/cm². For the first time, the degradation mechanisms of VDMOS devices under neutron irradiation during switching operations are systematically revealed: a 32–36% reduction in threshold voltage (with the main power transistor dropping from 5 V to 3.4 V) and an increase in on-resistance. Based on these findings, a selection criterion for power transistors is established, enabling the power supply to achieve a 2 W output in extreme environments such as nuclear power plant monitoring and satellite systems. The results provide a comprehensive solution for radiation-hardened power electronics systems, covering device characteristic analysis to circuit optimization, with significant engineering application value. Full article

Accurate pressure monitoring is crucial for both human body applications and intelligent robotic arms, particularly for whole-body motion monitoring in human–machine interfaces. Conventional wearable electronic devices, however, often suffer from rigid connections, non-conformity, and inaccuracies. In this study, we propose a high-precision wireless flexible sensor using a poly(vinyl alcohol)/single-walled carbon nanotube/MXene composite as the sensitive material, combined with a randomly distributed wrinkle structure to accurately monitor pressure parameters. To validate the sensor’s performance, it was used to monitor movements of the vocal cords, bent fingers, and human pulse. The sensor exhibits a pressure measurement range of approximately 0–130 kPa and a minimum resolution of 20 Pa. At pressures below 1 kPa, the sensor exhibits high sensitivity, enabling the detection of transient pressure changes. Within the pressure range of 1–10 kPa, the sensitivity decreases to approximately 54.71 kPa⁻¹. Additionally, the sensor demonstrates response times of 12.5 ms at 10 kPa. For wireless signal acquisition, the pressure sensor was integrated with a Bluetooth chip, enabling real-time high-precision pressure monitoring. A deep learning-based training model was developed, achieving over 98% accuracy in motion recognition without additional computing equipment. This advancement is significant for streamlined human motion monitoring systems and intelligent components. Full article

Silicon carbide (SiC) is a promising semiconductor material for electronics and photonics. Ultrafast laser processing of SiC enables three-dimensional nanostructuring, enriching and expanding the functionalities of SiC devices. However, challenges arise in delivering uniform, high-aspect-ratio (length-to-width) nanostructures due to difficulties in confining light energy at the nanoscale while simultaneously regulating intense photo modifications. In this study, we report the controllable growth of long-distance, high-straightness, and high-parallelism multifilament structures in SiC using ultrafast laser processing. The mechanism is the formation of femtosecond multifilaments through the nonlinear effects of clamping equilibrium, which allow highly confined light to propagate without diffraction in parallel channels, further inducing high-aspect-ratio nanostripe-like photomodifications. By employing an elliptical Gaussian beam—rather than a circular one—and optimizing pulse durations to stabilize multifilaments with regular positional distributions, the induced multifilament structures can reach a length of approximately 90 μm with a minimum linewidth of only 28 nm, resulting in an aspect ratio of over 3200:1. Raman tests indicate that the photomodified regions consist of amorphous SiC, amorphous silicon, and amorphous carbon, and photoluminescence tests reveal that silicon vacancy color centers could be induced in areas with lower light power density. By leveraging femtosecond multifilaments for diffraction-less light confinement, this work proposes an effective method for manufacturing deep-subwavelength, high-aspect-ratio nanostructures in SiC. Full article

Silicon (Si), the cornerstone semiconductor in the micro-electronics industry, can provide a cost-efficient platform with mature technologies for photodetection in visible and near-infrared regions. However, its intrinsic properties, such as a narrow bandgap and the shallow penetration depth of ultraviolet (UV) light into its surface with surface trap states, remain challenges, rendering it unsuitable for effective UV light detection. Various techniques have been reported to circumvent these surface defect-induced difficulties. In addition, wide-bandgap semiconductors that favor UV light absorption in a solar-blind way have been combined with Si for UV light detection in order to retain the device’s compatibility with Si-CMOS processes, though it still faces challenges that need to be overcome. This review starts with concepts of basic parameters of photodetectors and categorizes UV photodetectors according to their detection mechanisms. We also present a review of wide-bandgap semiconductor-based UV light detectors and those based on Si, with a discussion of surface defect minimization. In addition, we review the hybrid structure of the two kinds, i.e., wide-bandgap semiconductors and Si, and discuss their properties that produce synergistic effects. Lastly, we provide conclusions and outlooks for the possible development of next-generation UV light detectors based on Si. Full article

Gallium nitride high electron mobility transistors (GaN HEMTs), characterized by their extremely high switching speeds and superior high-frequency performance, have demonstrated significant advantages, and gained extensive applications in fields such as aerospace and high-power-density power supplies. However, their unique internal architecture renders these devices highly sensitive to circuit parasitic parameters. Conventional circuit design methodologies often induce severe issues such as overshoot and high-frequency oscillations, which significantly constrain the realization of their high-frequency performance. To solve this problem, this paper investigates the nonlinear dynamic behavior of GaN HEMTs during switching transients by establishing an equivalent impedance model. Based on this model, a detailed analysis is implemented to elucidate the mechanism by which RC Snubber circuits influence the system’s resonance frequency and the amplitude at the resonant frequency. Through this analysis, an optimal RC Snubber circuit parameter is derived, enabling effective suppression of high-frequency oscillations during the switching transient of GaN HEMT. Experimental results demonstrate that the proposed design achieves a maximum reduction of 40% in voltage overshoot, shortens the ringing time to one-twentieth of the original value, and suppresses noise by 20 dB in the high-frequency range of 20 MHz to 30 MHz, thereby significantly enhancing the stability and reliability of circuit operation. Additionally, considering the heat dissipation requirements in high power density scenarios, this work optimizes the layout of devices, and heat sinks to maintain operational temperatures within safe limits, further mitigating the impact of parasitic parameters on overall system performance. Full article

The large-scale utilization of wind and solar energy is crucial for achieving carbon neutrality targets. However, as extensive wind and solar power generation is integrated via power electronic devices, the inertia level of power systems continues to decline. This leads to a significant reduction in the system’s frequency regulation capability, posing a serious threat to frequency stability. Optimizing the system is an essential measure to ensure its safe and stable operation. Traditional optimization approaches, which separately optimize transmission and distribution systems, may fail to adequately account for the variability and uncertainty of renewable energy sources, as well as the impact of inertia changes on system stability. Therefore, this paper proposes a two-layer optimization method aimed at simultaneously optimizing the operation of transmission and distribution systems while satisfying minimum inertia constraints. The upper-layer model comprehensively optimizes the operational costs of wind, solar, and thermal power systems under the minimum inertia requirement constraint. It considers the operational costs of energy storage, virtual inertia costs, and renewable energy curtailment costs to determine the total thermal power generation, energy storage charge/discharge power, and the proportion of renewable energy grid connection. The lower-layer model optimizes the spatiotemporal distribution of energy storage units within the distribution network, aiming to minimize total network losses and further reduce system operational costs. Through simulation analysis and computational verification using typical daily scenarios, this model enhances the disturbance resilience of the transmission network layer while reducing power losses in the distribution network layer. Building upon this optimization strategy, the model employs multi-scenario stochastic optimization to simulate the variability of wind, solar, and load, addressing uncertainties and correlations within the system. Case studies demonstrate that the proposed model not only effectively increases the integration rate of new energy sources but also enables timely responses to real-time system demands and fluctuations. Full article

Cobalt-doped iron disulfide (FeS₂) thin films were synthesized via chemical bath deposition (CBD) followed by annealing at 450 °C, yielding phase-pure pyrite structures with multifunctional properties. A deposition temperature of 95 °C is critical for promoting Co incorporation, suppressing sulphur vacancies, and achieving structural stabilization of the film. After annealing, the dendritic morphologies transformed into compact quasi-spherical nanoparticles (~100 nm), which enhanced the crystallinity and optoelectronic performance of the films. The films exhibited strong absorption (>50%) in the visible and near-infrared regions and tunable direct bandgaps (1.14 to 0.96 eV, within the optimal range for single-junction solar cells. Electrical characterization revealed a fourth-order increase in conductivity after annealing (up to 4.78 Ω⁻¹ cm⁻¹) and confirmed stable p-type behavior associated with Co²⁺-induced acceptor states and defect passivation. These results demonstrate that CBD enabled the fabrication of Co-doped FeS₂ thin films with synergistic structural, electrical, and optical properties. The integration of earth-abundant elements and tunable electronic properties makes these films promising absorber materials for the next-generation photovoltaic devices. Full article

The enhancement effect and mechanism of porous frameworks on hydrogel thermal control performance are key factors in evaluating their engineering applications and performance improvements. This study investigates the enhancement mechanism of porous framework composite phase-change materials (CPCM) on hydrogel thermal control performance through multi-scale visualization comparison experiments. Results indicate that pure hydrogels, due to their dense internal structure, hinder water vapor escape, thereby impeding overall fluidity and mass transfer rates. The introduction of a porous framework significantly improves internal heat transfer and moisture transport pathways within the hydrogel, enabling smooth water vapor release during heating and preventing localized heat accumulation. Under 100 °C heating conditions, CPCM exhibited a 65% reduction in mass-specific dehydration rate compared to pure hydrogel, with a 25% lower temperature drop. Energy efficiency increased by 13.5% over hydrogel, while the coefficient of variation decreased by 34.1%, demonstrating superior thermal stability and temperature control capabilities. This study elucidates from a mechanistic perspective how porous frameworks regulate the thermal and mass transfer behaviors of hydrogels, providing a theoretical basis and experimental support for their advanced application and optimization in the thermal control systems of electronic devices. Full article