Search Results (8,128)

Air-cooled heat sinks remain a practical and cost-effective solution for thermal management in high power-density electronic systems. This study investigates the thermal–hydraulic performance of a plate pin-fin heat sink operating under forced convection, with emphasis on the coupled interaction between heat-transfer enhancement and pressure-drop penalty. The proposed hybrid configuration combines the low flow resistance of plate fins with the wake-induced mixing characteristics of pin-fin elements, thereby modifying boundary-layer development and flow structures within the fin channels. This review comprehensively analyzes existing experimental measurements across a range of Reynolds numbers to evaluate the average Nusselt number, thermal resistance, and friction factor. The results demonstrate that the inclusion of pin elements significantly enhances convective heat transfer through increased flow disruption and vortex formation, while incurring a moderate increase in pressure loss relative to conventional plate-fin designs. In addition, flow visualization and temperature mapping reveal improved heat transfer uniformity along the streamwise direction, particularly at intermediate Reynolds numbers where transition effects become pronounced. Empirical correlations were developed to relate the Nusselt number and friction factor to Reynolds number and key geometric ratios, providing predictive capability for thermo-hydraulic performance assessment. The findings indicate that fin-scale geometric optimization plays a dominant role in achieving improved overall performance and that the plate pin-fin configuration offers a favorable trade-off between heat-transfer augmentation and hydraulic efficiency for forced-convection electronic cooling applications. Full article

Under drip irrigation conditions, the transport pattern of soil water in the root zone directly affects the water use efficiency of crops. The type of soil matrix, initial moisture content, and irrigation water quality jointly determine the hydrodynamic process of water infiltration. However, as a special type of irrigation water, the water movement mechanism of biogas slurry under drip irrigation in soilless cultivation substrates still lacks systematic investigation. In this study, transparent soil column infiltration experiments were conducted using two types of cultivation substrates—organic (coconut coir) and inorganic (desert sand)—under controlled facility conditions. Three initial moisture contents (10%, 15%, and 20%) and two irrigation water qualities (tap water and diluted biogas slurry) were combined to form twelve treatment groups. Soil moisture sensors and visualization techniques were employed to quantitatively analyze the wetting front morphology, vertical and horizontal infiltration rates, wetting ratio, and soil moisture profile distribution under different treatments. The results showed that the initial moisture content significantly influenced the advancement pattern of the wetting front. Higher initial moisture levels promoted the transformation of the wetting front shape from a “semi-pear” form to a “hemispherical” one and reduced the rate of infiltration decline. The coconut coir substrate exhibited stronger vertical infiltration capacity and a central water aggregation characteristic, whereas the desert sand demonstrated a wider horizontal expansion range. Under low and moderate initial moisture conditions, the application of biogas slurry enhanced horizontal water diffusion and improved the uniformity of the wetted zone, with the wetting ratio increasing by more than 6% compared with high moisture conditions. In addition, the power function model provided an excellent fit for the cumulative infiltration process across all treatments (R² > 0.96), indicating its suitability for describing the water transport process in facility cultivation substrates. This study provides theoretical support for precise water and fertilizer management and the efficient utilization of biogas slurry in soilless cultivation systems. Full article

Nowadays, thermal runaway accidents involving lithium batteries in new energy vehicles and energy storage power stations occur frequently, with battery deformation pressure as the core precursor signal. Traditional battery protection schemes suffer from limitations, including wired connections, limited real-time remote monitoring, and insufficient sensing accuracy, rendering them unable to meet the safety monitoring needs of large-scale battery modules. Therefore, a high-precision pressure-sensing battery protection system based on the Internet of Things has been developed. This paper selects a MEMS high-precision pressure sensor with an accuracy of ±0.1 kPa to design an IoT sensing node based on the STM32L431 and LoRa/Wi-Fi 6, integrating pressure sensing and wireless communication. It proposes a sliding-average filtering and wavelet denoising algorithm, as well as a temperature-compensation calibration model, to optimize sensing accuracy. Additionally, it constructs a hierarchical early warning model based on pressure thresholds. The experiment demonstrates that the sensor achieves a detection accuracy of 99.2%, a response delay of less than 50 ms, a transmission packet loss rate of less than 0.5%, an end-to-end delay of less than 200 ms, and an early warning accuracy rate of 99.2% under battery overcharge/overtemperature conditions. The innovation of this study lies in the first integration of high-precision pressure sensing and IoT communication for battery protection. A low-power IoT sensing node tailored for battery aging scenarios has been designed, validating the novel application value of IoT sensing in the safety monitoring of new energy equipment. This system fills a gap in IoT pressure-sensing technology for battery protection, enabling practical applications and serving as a reference for implementing integrated sensing and communication technology. Full article

Nowadays, Additive Manufacturing for Electronics (AME) is gaining ground in device fabrication for the numerous advantages of these types of manufacturing technologies, such as fast production processes, freeform design, and low-cost prototyping. In this scenario, the proposed research work is focused on evaluating an innovative strategy for a common issue in power electronics, which is related to the generation of hotspots. To face this problem, the 3D printing of ceramic substrates with different high surface areas was studied to improve thermal dissipation. Together with improved thermal management, the upper surface of the devices enabled the deposition of a desired conductive pattern and the bonding of bare die components for device fabrication. Finally, thermal exchange was monitored to verify the efficacy and efficiency of the devices’ dissipation capabilities. The proposed models exhibited a 70% temperature reduction upon transitioning from air to water. Furthermore, the operating temperature remained stable for 10 min, meeting the specific requirements of the intended application. Full article

Electromagnetic attractive forming (EMAF), as an emerging branch of electromagnetic forming (EMF), has attracted increasing attention due to its unique capacity to shape workpieces toward the coil, offering distinct advantages in forming small-diameter tubes, repairing surface dents, and strengthening hole fasteners. This review systematically classifies and elaborates on the two main approaches for generating electromagnetic attractive force: (1) methods based on dual-frequency discharge and (2) methods based on low-frequency discharge. For each category, the working principles, key technological configurations, experimental verifications, and application scenarios are comprehensively discussed. The dual-frequency discharge approach, implemented through sequential dual-capacitor, dual-coil, and novel single-power circuits, enables controllable attractive forces for sheet/tube forming and hole-fastener strengthening. The low-frequency discharge approach, utilizing ferromagnetic effects, attractive screen, or current-phase-difference mechanisms, extends EMAF to ferromagnetic and non-ferromagnetic materials. Finally, the existing challenges and future research directions are outlined, aiming to provide clear research guidance for the in-depth development and practical engineering application of EMAF technology. Full article

Infrared thermography is a significant and extensively utilized method for assessing the operational condition of power equipment. Nonetheless, the constrained spatial resolution of infrared imaging systems, imaging noise, and the inadequate representational capacity of single-modality data render the precise segmentation of power equipment targets difficult, particularly in intricate backdrops and settings with weak structures. Simultaneously, obtaining high-quality pixel-level annotations for power equipment is expensive and laborious, leading to a scarcity of training samples and thus diminishing the efficacy of conventional supervised segmentation techniques. This research offers a super-resolution guided cross-modal segmentation strategy to tackle these issues in data-scarce circumstances and examines the applicability of the general-purpose segmentation model Segment Anything Model 3 (SAM3) for infrared image segmentation of power equipment. A super-resolution reconstruction framework based on a high-order degradation model is built to enhance low-resolution infrared images collected in real-world contexts. An Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) -based network incorporating residual-in-residual dense blocks (RRDB) is utilized to reconstruct infrared thermograms, hence improving structural features and boundary representations. Secondly, the concurrently obtained visible-light images are improved by low-light enhancement methods, and an anchor-free object detection framework is employed to ensure accurate localization of power equipment targets. The identified areas in visible images are aligned with the coordinate system of infrared super-resolution images via cross-modal geometric transformation, establishing a cross-modal spatial prior that efficiently limits the search space for infrared segmentation and mitigates background interference. The general-purpose segmentation model SAM3 is introduced, utilizing cross-modal detection boxes as prompts to facilitate precise segmentation of power equipment targets in infrared super-resolution images, achieving high-accuracy segmentation without the necessity for extensive task-specific annotated data. The experimental results demonstrate that our proposed approach significantly improves both the accuracy and robustness of infrared image segmentation for power equipment under complex conditions, attaining a Jaccard index of 89.86% and a Dice coefficient of 91.12%, thereby validating its efficacy and practical applicability in data-scarce environments. Full article

Estimating individual tree Above-Ground Biomass (AGB) is essential for assessing ecological functions and carbon storage in both forest and urban environments. Traditional field-based methods, such as plot measurements, are costly and impractical for large-scale applications. However, satellite- and aerial-based techniques lack the spatial resolution for individual-tree-level analysis. Unmanned Aerial Vehicle (UAV) Light Detection and Ranging (LiDAR) data, combined with machine learning (ML), offers a powerful alternative for detailed tree structure measurement and AGB estimation. Leveraging advances in deep-learning-based individual tree detection and geometric structure estimation including Height (H), Surface Area (SA), Volume (V), and Crown Width (CW), this study develops ML regression models for estimating individual tree AGB. We explore three objectives: (1) evaluating four regression models including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Feed-Forward Neural Network (FFNN); (2) sensitivity assessment of different geometric feature combinations on model accuracy; and (3) improving model robustness using Synthetic Minority Over-sampling Technique (SMOTE) data augmentation for addressing imbalanced data. Results show that the RF model outperforms others that achieved the lowest RMSE and most balanced residual distribution. CW was the strongest single predictor of AGB and, in combination with H, yielded to the most accurate results. This combination improved RMSE and R² by 14.2% and 89.3% with respect to single-variable-based models. The integration of SMOTE and RF further improved model performance since it lowered RMSE by 225.6 kg (~22.1%) and increased R² by 0.76 (~49.0%). This was particularly evident in underrepresented low and high AGB ranges. The proposed RF-SMOTE approach is a cost-effective and scalable approach for generating high-quality ground truth data to enable large-scale satellite-based biomass estimation and help forest carbon accounting and planning in cities and forests. Full article

Autosomal short tandem repeat (STR) markers remain the cornerstone of modern forensic genetics, providing exceptional power for individualization, kinship verification, and reconstruction of complex investigative cases. Over the last decade, the field has undergone a major technological transition from length-based capillary electrophoresis (CE) toward sequence-level characterization using massively parallel sequencing (MPS), enabling detection of internal sequence variants (isoalleles) and flanking-region polymorphisms that substantially increase discriminatory power in many forensic contexts. Although MPS is increasingly adopted in forensic laboratories, implementation remains dependent on infrastructure, cost considerations, validation requirements, and jurisdiction-specific legal frameworks. This review synthesizes the molecular mechanisms underlying STR variability, including replication slippage and mutation processes, and critically evaluates the transition to sequencing-based analysis. Particular attention is given to analytical challenges such as stochastic effects in ultra-low-template DNA and PCR inhibition in degraded samples. Special emphasis is placed on identification of skeletal remains from mass graves and historical contexts, where hierarchical analytical strategies—from mini-STR approaches to MPS-based workflows—enable recovery of highly fragmented DNA. The review also examines the evolution of probabilistic genotyping (PG), highlighting the importance of algorithmic transparency and reproducible analytical frameworks for judicial applications. By integrating technological advances with practical forensic challenges, this review outlines a comprehensive framework for implementing high-resolution STR analysis in contemporary genomic casework. As a narrative synthesis, the conclusions reflect currently available published evidence and acknowledge variability in validation status, implementation practices, and regional forensic infrastructures. Full article

This article presents an innovative methodology for assessing the durability of power engineering components under thermo-mechanical fatigue conditions. The approach integrates laboratory low-cycle fatigue tests of alloy specimens at elevated temperatures, measurements of working-medium parameters obtained from operating industrial equipment, and numerical simulations performed using the finite element method. Durability is estimated on the basis of curves describing the relationships between critical parameters such as the Coffin–Manson and Ostergren parameters and the number of cycles to failure. Within the region of the structure identified as the most susceptible to fatigue damage, the orientation of the critical plane is determined with respect to the corresponding criterion functions. This allows the calculated criterion values to be correlated with experimental data, enabling the determination of the incremental durability loss of the component. The proposed methodology is distinguished by its practical applicability and the possibility of incorporating both proprietary fatigue test results and data reported in the literature. Full article

Fine bubbles have attracted attention in recent years due to their promising characteristics and extensive applications. One type of fine bubble generator, the Venturi tube, utilizes a sudden change in pressure inside the tube and is widely used due to its simple structure, high generation efficiency, and low power consumption. The volume of bubbles generated (generation yield) and their average diameter are key parameters in evaluating the performance of a Venturi tube generator, which depends on both the flow conditions and the geometric configuration of the generator. In this study, an oral irrigator incorporating fine bubble technology was developed, with a Venturi tube embedded in the irrigator for fine bubble generation. We designed Venturi tubes with various geometric configurations under different flow conditions to enhance fine bubble generation performance and cleaning efficiency through both experiments and numerical simulations. The results indicate that the generation performance and cleaning performance of fine bubbles are strongly influenced by the geometric parameters of the Venturi tube. Among the tested configurations, the Venturi tube with a divergent angle of 5° and a divergent length of 30 mm demonstrated the best performance. Full article

Molybdenum disulfide (MoS₂) films are promising solid lubricants for aerospace and other advanced applications, yet their tribological performance is highly sensitive to environmental conditions. To enhance environmental adaptability, Zr-doped MoS₂ composite films were prepared by magnetron co-sputtering, and their composition, microstructure, mechanical properties, and tribological behavior were systematically investigated. The results showed that the as-deposited MoS₂ films exhibited a nearly stoichiometric sulfur-to-molybdenum ratio (S/Mo ≈ 2), while the Zr-doped MoS₂ composite films showed sulfur-deficient, sub-stoichiometric ratios (S/Mo < 2). Pure MoS₂ films displayed a porous columnar structure, whereas with the incorporation of Zr, the columnar structure becomes progressively more compact. Moreover, the film structure transitions from a purely crystalline form to a two-phase structure with both crystalline and amorphous phases coexisting. The hardness and elastic modulus of the films increased with the addition of Zr, mainly due to the densification of the structure and the disorder introduced in the film. Moderate Zr doping markedly improved the friction and wear performance of composite films across vacuum, atmospheric, and humid environments. The optimal film achieved a coefficient of friction (COF) of 0.02 and wear rate of 6.23 × 10⁻⁸ mm³/N·m in vacuum and COFs of 0.10 with low wear rates in both atmospheric and humid conditions. By adjusting the Zr target power to modulate Zr content, the crystallographic orientation and microstructure of MoS₂-Zr composite films could be tailored, thereby regulating their mechanical and tribological properties. This study provides theoretical guidance for the application of metal-doped MoS₂ composite films under alternating environmental conditions. Full article

AgriRover was developed to address key operational constraints faced by smallholder vineyards in Peru, including sandy and saline soils, labor shortages, and limited access to advanced agricultural machinery. The platform features an articulated, all-wheel-drive chassis designed to ensure mobility and stability on loose terrain while minimizing soil compaction. This study presents the simulation-driven development of a digital pre-twin, conceived as a virtual prototype prepared for future sensor integration but currently operating without real-time data feedback. The pre-twin was implemented in MATLAB/Simulink (vers. 2024b) using a multibody dynamics model and evaluated through eight scenario-based simulations, varying field geometry, soil type, and slope conditions. The results show stable operation on slopes up to 10°, wheel sinkage values ranging between approximately 20 and 45 mm depending on terrain conditions, and a moderate battery state-of-charge reduction across most scenarios, with higher power demand observed on sandy soils. A scenario-based comparison indicates a potential reduction of approximately 50% in total monitoring time relative to manual field scouting, while advanced sensing, autonomous navigation, and AI-based analytics remain part of future developments. The current pre-twin provides a validated, low-cost foundation for context-specific phenological monitoring and early-stage precision agriculture applications in developing regions. Full article

Axially chiral compounds, indispensable in asymmetric catalysis, drug discovery, and materials science, have witnessed transformative advancements in synthesis through organocatalytic kinetic resolution (OKR) over the past decade. This review systematically dissects the latest achievements (2010–2025) in OKR, focusing on catalyst design, mechanistic insights, substrate diversification, and synthetic applications across C–C biaryl, C–N heterobiaryl, and olefinic axially chiral frameworks. By harnessing non-covalent interactions, OKR has emerged as a powerful strategy to overcome the challenges of low rotational barriers and limited stereocontrol, offering sustainable and enantioselective access to privileged chiral scaffolds. Furthermore, the current challenges and future prospects in this rapidly evolving field are assessed. Full article

Spectrometers are essential tools for revealing the interaction between light and matter and analyzing the composition and state of materials, widely employed in scientific research, industrial inspection, and biomedicine applications. With the continuous expansion of application scenarios, higher demands are placed on the miniaturization, integration, and portability of spectrometers. This paper proposes and implements a reconfigurable silicon photonic on-chip spectrometer based on cascaded multi-stage Mach–Zehnder interferometers (MZIs). This structure achieves efficient sampling of the input spectrum by applying adjustable phase shifts to each MZI stage to construct different spectral responses. Combined with a convex optimization algorithm incorporating differential operators, the unknown input signals are decomposed into sparse and smooth components, achieving high-accuracy reconstruction. Experimental results show that the proposed five-stage MZI design with a total of 216 sampling channels achieves a spectral reconstruction resolution of 5 pm over the wavelength range from 1500 nm to 1600 nm. Moreover, the spectrometer exhibits consistently low reconstruction errors for broadband spectra, sparse spectra, and their hybrid spectral profiles. This research demonstrates excellent comprehensive performances in device structure design, phase modulation strategy, and reconstruction algorithm, providing an effective solution for realizing low-power, small-footprint, and high-precision on-chip spectral analysis. Full article

Capacitive Power Transfer (CPT) technology, as an emerging wireless power supply solution, exhibits great potential in areas such as electric vehicle charging, underwater equipment power supply, biomedical implants, and consumer electronics due to its advantages of low cost, light weight, insensitivity to metals, and potential high power density. However, the coupling capacitance is susceptible to the influence of transmission distance, misalignment, and changes in environmental media, leading to fluctuations in system output characteristics and becoming a key challenge restricting its application. This report aims to systematically review the key technological advancements proposed in recent years to achieve constant voltage/current/power output and enhance system robustness. Firstly, this study categorically reviews the CPT system topologies for constant voltage output, constant current output, and constant power output, analyzing the principles, advantages, and disadvantages of achieving load-independent or coupling-independent output. Secondly, it sorts out various active and passive control strategies, including frequency regulation, impedance matching, adaptive parameter switching, and pulse modulation, which are used to manage dynamic changes. Next, it summarizes innovative design and optimization methods for couplers tailored to specific application scenarios, such as large-gap electric vehicle charging, underwater, and rotating mechanisms. Finally, based on existing research, this review describes the challenges that CPT technology still faces in achieving efficient, high-power, and highly robust constant output, and looks forward to future research directions. Full article