Search Results (25,700)

Direct copper-plated ceramic (DPC) substrates have emerged as a favored solution for power device packaging due to their unique technical advantages. AuSn, characterized by its high hermeticity and environmental adaptability, represents the optimal sealing technology for DPC substrates. Through the application of vacuum sintering techniques and adjustment of peak temperatures (325 °C, 340 °C, and 355 °C), the morphology and composition of interfacial compounds were systematically investigated, along with an analysis of their formation mechanisms. A gradient aging experiment was designed (125 °C/150 °C/175 °C × oxygen/argon dual atmosphere × 600 h) to elucidate the synergistic effects of environmental temperature and atmosphere on the growth of intermetallic compounds (IMCs). The results indicate that the primary reaction in the sealing weld seam involves Ni interacting with Au-Sn to form (Ni, Au)₃Sn₂ and Au₅Sn. However, upon completion of the sealing process, this reaction remains incomplete, leading to a coexistence state of (Ni, Au)₃Sn₂, Au₅Sn, and AuSn. Additionally, Ni diffuses into the weld seam center via dendritic fracture and locally forms secondary phases such as δ(Ni) and ζ’(Ni). These findings suggest that the weld seam interface exhibits a complex, irregular, and asymmetric microstructure comprising multiple coexisting compounds. It was determined that Tpeak = 325 °C to 340 °C represents the ideal welding temperature range, where the weld seam morphology, width, and Ni diffusion degree achieve optimal states, ensuring excellent device hermeticity. Aging studies further demonstrate that IMC growth remains within controllable limits. These findings address critical gaps in the understanding of the microstructural evolution and interface characteristics of asymmetric welded joints formed by multi-material systems. Full article

Mars has been a primary focus of planetary science, with significant advancements over the past two decades across disciplines including geological evolution, surface environment, and atmospheric and space science. However, the rapid growth of the related literature has rendered traditional manual review methods increasingly inadequate. This inadequacy is particularly evident in interdisciplinary research, which is often characterized by dispersed topics and complex semantics. To address this challenge, this study proposes an automated analysis framework based on natural language processing (NLP) to systematically review the Martian research in Earth and space science over the past two decades. The research database contains 151,196 Mars-related sentences extracted from 10,655 publications spanning 2001 to 2024. Using machine learning techniques, the framework clusters Mars-related sentences into semantically coherent groups and applies topic modeling to extract core research themes. It then analyzes their temporal evolution across the Martian solid, surface, atmosphere, and space environments. Finally, through sentiment analysis and semantic matching, it highlights unresolved scientific questions and potential directions for future research. This approach offers a novel perspective on the knowledge structure underlying Mars exploration and demonstrates the potential of NLP for large-scale literature analysis in planetary science. The findings potentially provide a structured foundation for building an interdisciplinary, peer-reviewed Mars knowledge base, which may inform future scientific research and mission planning. Full article

X-ray and EUV solar flare emission cause increases in the Earth’s dayside ionospheric electron density. While the response of the lower ionosphere to X-rays is well studied, the delay between EUV flare emission and the response of the ionospheric F-region has not been investigated. Here, we calculate the delays between incident He II 304 Å emission, and the TEC response for 10 powerful solar flares, all of which exhibit delays under 1 min. We assess these delays in relation to multiple solar and geophysical factors, and find a strong negative correlation (∼−0.85) between delay and He II flux change and a moderate negative correlation (∼−0.55) with rate of increase in He II flux. Additionally, flare magnitude and the X-ray-to-He II flux ratio at peak He II emission show strong negative correlations with delay (∼−0.80 and ∼−0.75, respectively). We also identify longer delays for flares occurring closer to the summer solstice. These results may have applications in upper-ionospheric recombination rate calculations, atmospheric modelling, and other solar–terrestrial studies. We highlight the importance of incident EUV and X-ray flux parameters on the response time of the ionospheric electron content, and these findings may also have implications for mitigating disruptions in communication and navigation systems. Full article

It has long been accepted that breathing gases that are physiologically inert include helium (He), neon (Ne), nitrogen (N₂), argon (Ar), krypton (Kr), xenon (Xe), and hydrogen (H₂). The term “inert gas” has been used to describe them due to their unusually high chemical stability. However, as investigations have advanced, many have shown that inert gas can have specific biological impacts when exposed to high pressure or atmospheric pressure. Additionally, different inert gases have different effects on intracellular signal transduction, ion channels, and cell membrane receptors, which are linked to their anesthetic and cell protection effects in normal or pathological processes. Through a selective analysis of the representative literature, this study offers a concise overview of the state of research on the biological impacts of inert gas and their molecular mechanisms. Full article

Poly(vinyl chloride) (PVC) undergoes thermal degradation during processing and operation, which necessitates the use of effective thermal stabilizers. The purpose of this work is to comprehensively evaluate the potential of new hierarchically structured titanium phosphates (TiP) with controlled morphology as thermal stabilizers of plasticized PVC, focusing on the effect of morphology and Ti/P ratio on their stabilizing efficiency. The thermal stability of the compositions was studied by thermogravimetric analysis (TGA) in both inert (Ar) and oxidizing (air) atmospheres. The effect of TiP concentration and its synergy with industrial stabilizers was analyzed. An assessment of the key degradation parameters is given: the temperature of degradation onset, the rate of decomposition, exothermic effects, and the carbon residue yield. In an inert environment, TiPMSI/TiPMSII microspheres demonstrated an optimal balance by increasing the temperature of degradation onset and the residual yield while suppressing the rate of decomposition. In an oxidizing environment, TiPR rods and TiPMSII microspheres provided maximum stability, enhancing resistance to degradation onset and reducing the degradation rate by 10–15%. Key factors of effectiveness include ordered morphology (spheres, rods); the Ti-deficient Ti/P ratio (~0.86), which enhances HCl binding; and crystallinity. The stabilization mechanism of titanium phosphates is attributed to their high affinity for hydrogen chloride (HCl), which catalyzes PVC chain scission, a catalyst for the destruction of the PVC chain. The unique microstructure of titanium phosphate provides a high specific surface area and, as a result, greater activity in the HCl neutralization reaction. The formation of a sol–phosphate framework creates a barrier to heat and oxygen. An additional contribution comes from the inhibition of oxidative processes and the possible interaction with unstable chlorallyl groups in PVC macromolecules. Thus, hierarchically structured titanium phosphates have shown high potential as multifunctional PVC thermostabilizers for modern polymer materials. Potential applications include the development of environmentally friendly PVC formulations with partial or complete replacement of toxic stabilizers, the optimization of thermal stabilization for products used in aggressive environments, and the use of hierarchical TiP structures in flame-resistant and halogen-free PVC-based compositions. Full article

In this study, we investigated the effects of air packaging, vacuum packaging and modified atmosphere packaging (CO₂/N₂: 80/20) on the purine metabolism and enzyme activities of refrigerated large yellow croakers. The results showed that modified atmosphere packaging significantly inhibited microbial growth, delayed adenosine triphosphate degradation and maintained higher IMP content (1.93 μmol/g on day 21) compared to the air packaging group (2.82 μmol/g on day 12). The total purine content increased with storage time, with hypoxanthine content increasing significantly and occupying most of the total content, which was the key factor for the elevation of purine, followed by adenine content showing a significant decreasing trend. Hypoxanthine accumulation was significantly suppressed in the modified atmosphere packaging group (2.31 μmol/g on day 18), which was much lower than that in the air packaging group (5.64 μmol/g), whereas xanthine and guanine did not show significant differences among the groups. The key enzymes xanthine oxidase and purine nucleoside phosphorylase were much less active in modified atmosphere packaging, effectively delaying the cascade reaction of inosine monophosphate → hypoxanthine → xanthine. The study confirmed that modified atmosphere packaging intervenes in purine metabolism through enzyme activity regulation, providing a theoretical basis for the preservation of low purine aquatic products. Full article

The complex system of high-entropy materials makes it challenging to reveal the specific function of each site for oxygen evolution reaction (OER). Here, with nickel foam (NF) as the substrate, FeCoNiCrMo/NF is designed to be prepared by metal–organic frameworks (MOF) as a precursor under an argon atmosphere. XRD analysis confirms that it retains a partial MOF crystal structure (characteristic peak at 2θ = 11.8°) with amorphous carbon (peaks at 22° and 48°). SEM-EDS mapping and XPS demonstrate uniform distribution of Fe, Co, Ni, Cr, and Mo with a molar ratio of 27:24:30:11:9. Electrochemical test results show that FeCoNiCrMo/NF has excellent OER characteristics compared with other reference prepared samples. FeCoNiCrMo/NF has an overpotential of 285 mV at 100 mA cm⁻² and performs continuously for 100 h without significant decline. The OER mechanism of FeCoNiCrMo/NF further reveal that Co and Ni are true active sites, and the dissolution of Cr and Mo promote the conversion of active sites into MOOH following the lattice oxygen mechanism (LOM). The precipitation–dissolution equilibrium of Fe also plays an important role in the OER process. The study of different reaction sites in complex systems points the way to designing efficient and robust catalysts. Full article

The safety of lithium-ion batteries during transportation is critically important. However, current standards exhibit limitations, as their environmental testing parameter thresholds fail to fully encompass actual transportation conditions. To enhance both safety and standard applicability, in this study, we focused on four representative environmental conditions: temperature, vibration, shock, and low atmospheric pressure. Field measurements were conducted across road, rail, and air transport modes using a self-developed data acquisition system based on the NearLink communication technology. The measured data were then compared with the threshold values defined in current international and national standards. The results reveal that certain measured values exceeded the upper limits prescribed by existing standards, indicating limitations in their applicability under extreme transport conditions. Based on these findings, we propose revised testing parameters that better reflect actual transport risks, including a temperature cycling range of 72 ± 2 °C (high) and −40 ± 2 °C (low), a shock acceleration limit of 50 gn, adjusted peak frequencies in the vibration PSD profile, and a minimum pressure threshold of 11.6 kPa. These results provide a scientific basis for optimising safety standards and improving the safety of lithium-ion battery transportation. Full article

Free-space optical (FSO) communications have emerged as a promising complement to conventional radio-frequency (RF) systems due to their high bandwidth, low interference, and license-free spectrum. Visible-light FSO communication, using laser diodes or LEDs, offers potential for short-range data links, but performance is highly wavelength-dependent under varying atmospheric conditions. This study presents an experimental evaluation of three visible laser diodes at 650 nm (red), 532 nm (green), and 405 nm (violet), focusing on their optical output power, quantum efficiency, and modulation behavior across a range of driving currents and frequencies. A custom laboratory testbed was developed using an Atmega328p microcontroller and a Visual Basic control interface, allowing precise control of current and modulation frequency. A silicon photovoltaic cell was employed as the optical receiver and energy harvester. The results demonstrate that the 650 nm red laser consistently delivers the highest quantum efficiency and optical output, with stable performance across electrical and modulation parameters. These findings support the selection of 650 nm as the most energy-efficient and versatile wavelength for short-range, cost-effective visible-light FSO communication. This work provides experimentally grounded insights to guide wavelength selection in the development of energy-efficient optical wireless systems. Full article

A number of phenomena were observed in experiments on the study of cosmic rays at mountain altitudes and in the stratosphere at ultra-high energies; in particular, the coplanarity of the most energetic particles and local subcascades in the so-called families of γ-rays and hadrons in the cores of extensive air showers at E₀ ≳ 2·10¹⁵ eV (√s ≳ 2 TeV). These effects are not described by theoretical models. To explain this phenomenon, it may be necessary to introduce a new process of generating the most energetic particles in the interactions of hadrons with the nuclei of atmospheric atoms. A new experimental array of cosmic ray detectors, including the ADRON-55 ionization calorimeter, has been created to study processes in EAS cores at ultra-high energies. The possibility of using it to study the coplanarity effect is being considered. Full article

This paper proposes an intelligent power adaptation framework for Free-Space Optics (FSO) communication systems operating under different weather conditions exploiting a deep learning (DL) analysis of received eye diagram images. The system incorporates two Convolutional Neural Network (CNN) architectures, LeNet and Wide Residual Network (Wide ResNet) algorithms to perform regression tasks that predict received signal quality metrics such as the Quality Factor (Q-factor) and Bit Error Rate (BER) from the received eye diagram. These models are evaluated using Mean Squared Error (MSE) and the coefficient of determination (${\mathrm{R}}^2$ score) to assess prediction accuracy. Additionally, a custom CNN-based classifier is trained to determine whether the BER reading from the eye diagram exceeds a critical threshold of ${10}^{-4}$; this classifier achieves an overall accuracy of 99%, correctly detecting 194/195 “acceptable” and 4/5 “unacceptable” instances. Based on the predicted signal quality, the framework activates a dual-amplifier configuration comprising a pre-channel amplifier with a maximum gain of 25 dB and a post-channel amplifier with a maximum gain of 10 dB. The total gain of the amplifiers is adjusted to support the operation of the FSO system under all-weather conditions. The FSO system uses a 15 dBm laser source at 1550 nm. The DL models are tested on both internal and external datasets to validate their generalization capability. The results show that the regression models achieve strong predictive performance, and the classifier reliably detects degraded signal conditions, enabling the real-time gain control of the amplifiers to achieve the quality of transmission. The proposed solution supports robust FSO communication under challenging atmospheric conditions including dry snow, making it suitable for deployment in regions like Northern Europe, Canada, and Northern Japan. Full article

UAV-based inspections are an effective way to ensure railway safety and have gained significant attention. However, images captured during complex weather conditions, such as rain, snow, or fog, often suffer from severe degradation, affecting image recognition accuracy. Existing algorithms for removing rain, snow, and fog have two main limitations: they do not adaptively learn features under varying weather complexities and struggle with managing complex noise patterns in drone inspections, leading to incomplete noise removal. To address these challenges, this study proposes a novel framework for removing rain, snow, and fog from drone images, called WeatherClean. This framework introduces a Weather Complexity Adjustment Factor (WCAF) in a parameterized adjustable network architecture to process weather degradation of varying degrees adaptively. It also employs a hierarchical multi-scale cropping strategy to enhance the recovery of fine noise and edge structures. Additionally, it incorporates a degradation synthesis method based on atmospheric scattering physical models to generate training samples that align with real-world weather patterns, thereby mitigating data scarcity issues. Experimental results show that WeatherClean outperforms existing methods by effectively removing noise particles while preserving image details. This advancement provides more reliable high-definition visual references for drone-based railway inspections, significantly enhancing inspection capabilities under complex weather conditions and ensuring the safety of railway operations. Full article

The formation and evolution of haze layers in planetary atmospheres play a critical role in shaping their chemical composition, radiative balance, and optical properties. In the outer solar system, the atmospheres of Titan and the giant planets exhibit a wide range of compositional and seasonal variability, creating environments favorable for the production of complex organic molecules under low-temperature conditions. Among them, Uranus—the smallest of the ice giants—has, since Voyager 2, emerged as a compelling target for future exploration due to unanswered questions regarding the composition and structure of its atmosphere, as well as its ring system and diverse icy moon population (which includes four possible ocean worlds). Titan, as the only moon to harbor a dense atmosphere, presents some of the most complex and unique organics found in the solar system. Central to the production of these organics are chemical processes driven by low-energy photons and electrons (<50 eV), which initiate reaction pathways leading to the formation of organic species and gas phase precursors to high-molecular-weight compounds, including aerosols. These aerosols, in turn, remain susceptible to further processing by low-energy UV radiation as they are transported from the upper atmosphere to the lower stratosphere and troposphere where condensation occurs. In this review, I aim to summarize the current understanding of low-energy (<50 eV) photon- and electron-induced chemistry, drawing on decades of insights from studies of Titan, with the objective of evaluating the relevance and extent of these processes on Uranus in anticipation of future observational and in situ exploration. Full article

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

The Sichuan Basin is a natural-gas-exploiting area with intensive agriculture activities. However, the spatial and temporal distribution of atmospheric methane concentration and the relationships with intensive agriculture and natural gas extraction activities are not well investigated. In this study, a long-term (2003–2021) dataset of column-averaged dry-air mole fraction of methane (XCH₄) over the Sichuan Basin and adjacent regions was built by integrating multi-satellite remote sensing data (SCIAMACHY, GOSAT, Sentinel-5P), which was calibrated using ground station data. The results show a strong correlation and consistency (R = 0.88) between the ground station and satellite observations. The atmospheric CH₄ concentration of the Sichuan Basin showed an overall higher level (around 20 ppb) than that of the whole of China and an increasing trend in the rates, from around 2.27 ppb to 10.44 ppb per year between 2003 and 2021. The atmospheric CH₄ concentration of the Sichuan Basin also exhibits clear seasonal changes (higher in the summer and autumn and lower in the winter and spring) with a clustered geographical distribution. Agricultural activities and natural gas extraction contribute significantly to atmospheric methane concentrations in the study area, which should be considered in carbon emission management. This study provides an effective way to investigate the spatiotemporal distribution of atmospheric CH₄ concentration and related factors at a regional scale with natural and human influences using multi-source satellite remote sensing data. Full article