Search Results (148)

Rapid removal of chemically diverse organic pollutants remains a major challenge in aqueous decontamination. In this study, atmosphere-controlled defect engineering was used to activate anatase TiO₂ as a rapid adsorbent operating on the minute scale, exhibiting low charge selectivity under the investigated conditions. A reduced black TiO₂ (B–TiO₂), produced by inert annealing, achieved ≈100% removal of cationic methylene blue within ~6 min and ≈91% uptake of anionic methyl orange within ~3 min, whereas pristine and air-annealed TiO₂ showed only marginal adsorption under identical conditions. Correlative structural and surface-sensitive analyses indicated that this behaviour was associated with a chemically activated near-surface region enriched in reduced titanium contributions, defect-associated or non-lattice oxygen environments and a locally perturbed anatase framework, together with finely dispersed carbon-related motifs integrated within the oxide matrix. Adsorption kinetics were described, within experimental resolution, by pseudo-second-order fitting, while intraparticle diffusion analysis supported sequential regimes initiated by rapid interfacial attachment. Equilibrium analysis yielded apparent maximum capacities of 6.116 mg g⁻¹ for methylene blue and 2.950 mg g⁻¹ for methyl orange, reflecting adsorption governed by surface heterogeneity for cationic species and an apparent saturation-type response for anionic uptake. Overall, controlled surface non-stoichiometry emerges as a viable strategy to enhance adsorption kinetics in TiO₂, providing a transferable design framework for developing oxide-based adsorbents for sustainable water-treatment applications. Full article

Long-term wind speed changes over the Yangtze River waterway have critical implications for inland shipping efficiency, emission dispersion, and renewable energy potential. This study utilizes a high-resolution 5 km gridded reanalysis dataset spanning 1979–2018 to conduct a comprehensive spatiotemporal analysis of surface wind climatology, variability, and trends along China’s primary inland waterway. A pivotal regime shift was identified around 2000, marking a transition from terrestrial stilling to a recovery phase characterized by wind speed intensification. Multiple change-point detection algorithms consistently identify 2000 as a pivotal turning point, marking a transition from the late 20th century “terrestrial stilling” to a recovery phase characterized by wind speed intensification. Post-2000 trends reveal pronounced spatial heterogeneity: the upstream section exhibits sustained strengthening (+0.02 m/s per decade, p = 0.03), the midstream shows weak or non-significant trends with localized afternoon stilling in complex terrain (−0.08 m/s per decade), while the downstream coastal zone demonstrates robust intensification exceeding +0.10 m/s per decade during spring–autumn daytime hours. Three distinct wind regimes emerge along the 3000 km corridor: a high-energy maritime-influenced downstream sector (annual means > 3.9 m/s, diurnal peaks > 6.0 m/s) dominated by sea breeze circulation, a transitional midstream zone (2.3–2.7 m/s) exhibiting bimodal spatial structure and unique summer-afternoon thermal enhancement, and a topographically suppressed upstream region (<2.0 m/s) punctuated by pronounced channeling effects through the Three Gorges constriction. Critically, the observed recovery contradicts widespread basin greening (97.9% of points showing significant positive NDVI trends), which theoretically should enhance surface roughness and suppress wind speeds. Correlation analysis reveals that wind variability is systematically controlled by large-scale atmospheric circulation patterns, including the Northern Hemisphere Polar Vortex (r ≈ 0.35), Western Pacific Subtropical High (r ≈ 0.38), and East Asian monsoon systems (r > 0.60), with distinct seasonal phase-locking between baroclinic spring dynamics and monsoon-thermal summer forcing. These findings establish a comprehensive, fine-scale climatological baseline essential for optimizing pollutant dispersion modeling, and evaluating wind-assisted propulsion feasibility to support shipping decarbonization goals along the Yangtze Waterway. Full article

Invasive insects increasingly threaten ecosystems worldwide, with wetlands especially vulnerable to unpredictable climate. Phragmites australis is a dominant plant species in Louisiana’s Mississippi River Delta and a critically important component of the wetland ecosystem. However, the invasive scale insect, Nipponaclerda biwakoensis, has contributed to large-scale dieback of this foundation species, jeopardizing erosion control, water filtration, and wildlife habitat. Despite rapid regional spread, the fine-scale dispersal of N. biwakoensis within host plants remains poorly understood. We examined whether the crawler-stage of N. biwakoensis scales preferentially settled on the bottom or top sections of P. australis stems, and whether plant nutritional and/or defensive traits shaped this preference. In field surveys, scale densities varied along the length of P. australis stems, with gravid females occurring 3.5× more frequently at the stem base than at the top; parasitism rates were similarly elevated, reaching 12× higher at the base. To evaluate potential drivers of this pattern, we quantified carbon, nitrogen, water, and phenolic content in lower and upper stem tissues and conducted complementary laboratory assays to test crawler settlement preferences. Under controlled conditions, crawlers settled most densely on middle stem sections, with lower densities at the base and the fewest near the top. The basal sections also contained 50% less nitrogen and 47% lower phenolic concentrations compared to the upper stem. The divergence in crawler settlement patterns between field and controlled conditions likely reflects the influence of additional environmental factors present in the field—such as habitat structure, microclimate, and natural enemies—that are absent or minimized in laboratory conditions. By applying a trait-based approach to insect dispersal, we link plant functional traits to N. biwakoensis crawler settlement patterns, strengthening our understanding of of insect distribution and guiding predictions of long-term dispersal in N. biwakoensis. Full article

High-voltage bushings are critical insulation components, yet conventional PRPD-based severity assessment methods that rely on global pattern morphologies such as “rabbit ears” and “tortoise shell” remain coarse, lack local sensitivity, and fail to track continuous degradation. This paper proposes a dynamic severity assessment method that shifts the focus from global contours to dense partial discharge (PD) clusters, defined as high-density aggregations of PD pulses in specific phase–magnitude regions of PRPD patterns. Each dense cluster is treated as the statistical projection of a physical discharge channel, and the evolution of its number, intensity, location, and shape provides a fine-scale description of defect development. A multi-level relative density and morphological image processing algorithm is used to extract dense clusters directly from PRPD histograms, followed by a 20-dimensional feature set and a five-index system describing discharge activity, development speed, complexity, instability, and evolution trend. A fuzzy comprehensive evaluation model further converts these indices into three severity levels with confidence measures. Long-term degradation tests on defective bushings demonstrate that the proposed method captures key turning points from dispersed multi-cluster patterns to a single dominant cluster and yields a stable, stage-consistent severity evaluation, offering a more sensitive and physically interpretable tool for condition monitoring and early warning of HV bushings. The method achieved a high evaluation confidence (average 60.1%), which rose to 100% at the critical failure stage. It successfully identified three distinct degradation stages (stable, accelerated, and critical) across the 49 test intervals. A quantitative comparison demonstrated significant advantages: 8.3% improvement in early warning (4 windows earlier than IEC 60270), 50.6% higher monotonicity, 125.2% better stability, and 45.9% wider dynamic range, while maintaining physical interpretability and requiring no training data. Full article

The article presents the results of a study on the production of a complex chromium–manganese–silicon-containing ferroalloy in a large-scale laboratory ore-thermal furnace using man-made waste—chromium-containing aspiration dust obtained during smelting of high-carbon ferrochrome, fines (−5 mm) of iron–manganese ore currently stored in landfills, and finely dispersed coal sludge formed during enrichment. A single-stage technology for the production of a new complex chromium–manganese–silicon-containing ferroalloy by carbothermal reduction is proposed. A metallurgical assessment of the initial charge materials was carried out by the X-ray diffraction (XRD) phase analysis, and metal samples of the obtained ferroalloy were studied by scanning electron microscopy (SEM) in combination with energy dispersive spectroscopy (EDS). The resulting ferroalloy has a complex microstructure with a predominance of carbide and intermetallic phases. A high degree of extraction of chromium (up to 80%), manganese (up to 75%), and silicon (up to 35%) was recorded. The average chemical composition of the obtained ferroalloy, wt.%: Cr—37.41; Mn—17.31; Si—11.84; C—3.81; P—0.14; S—0.02. The slag formed during the smelting of the ferroalloy has satisfactory technological properties: it is characterized by good fluidity, and it actively exits the furnace by gravity. Entanglement of metal kings in the slag is not observed. The results obtained confirm the technological feasibility of the utilization of technogenic raw materials for the production of complex ferroalloys of the FeCrMnSi type. Full article

We report a scalable route to hybrid aluminum matrix composites (AMCs) based on Al6060 (as-fabricated condition) reinforced with 2 wt.% TiB₂ and 1 wt.% microsilica, fabricated by ultrasonically assisted stir casting (UASC) followed by radial-shear rolling (RSR). Premixing and preheating of powders combined with acoustic cavitation/streaming during UASC ensured uniform, non-sedimentary particle dispersion and low-defect cast billets. X-ray diffraction of the as-cast composite shows fcc-Al with weak TiB₂ reflections and no reaction products; microsilica remains amorphous. Electron microscopy and EBSD after RSR reveal full erasure of cast dendrites, fine equiaxed grains, weakened texture, and a high fraction of high-angle boundaries due to the concurrent action of particle-stimulated nucleation (micron-scale TiB₂) and Zener pinning/Orowan strengthening (50–350 nm microsilica). Mechanical testing shows that, in the cast state—comparing cast monolithic Al6060 to the cast hybrid-reinforced composite—yield strength (YS) increases from 61.7 to 77.2 MPa and ultimate tensile strength (UTS) from 103.4 to 130.7 MPa, without loss of ductility. After RSR to Ø16 mm (cumulated true strain ≈ 0.893), the hybrid attains YS 101.2 MPa, UTS 150.6 MPa, and elongation ≈ 22.0%, i.e., comparable strength to rolled Al6060 (UTS 145.1 MPa) while restoring/raising ductility by ~9.7 percentage points. Microhardness follows the same trend, increasing from 50.2 HV0.2 to 73.1 HV0.2 when comparing the base cast condition with the rolled hybrid. The route from UASC to RSR thus achieves a favorable mechanical strength–ductility balance using an economical, eco-friendly oxide/boride hybrid reinforcement, making it attractive for formable AMC bar and rod products. Full article

High-efficiency diesel and lean-burn engines produce lower exhaust temperatures, which can delay the activation of after-treatment catalysts such as Diesel Oxidation Catalysts (DOCs). This study explores ion beam sputtering as a post-synthesis strategy to enhance the low-temperature activity of commercial Pt/CeO₂–ZrO₂ catalysts. Low-energy ions (0.5–1.5 keV) were applied with controlled variations in treatment number, beam current, and exposure time to selectively generate oxygen vacancies and improve Pt dispersion. Structural and chemical effects were characterized using X-ray diffraction (XRD), BET surface area measurements, X-ray photoelectron spectroscopy (XPS) and extended X-ray absorption fine structure (EXAFS). Catalytic performance was evaluated through CO and C₃H₆ oxidation under conditions mimicking lean-burn engine exhaust. Increasing the number of ion treatments progressively lowered light-off temperatures, correlating with enhanced Pt–Ce³⁺ interactions and improved surface reducibility. Variations in beam current and exposure time further modulated these surface effects, confirming the tunable nature of the approach. The results demonstrate that ion beam sputtering selectively modifies the catalyst surface without altering the bulk structure, directly linking atomic-scale modifications to improved low-temperature activity. This strategy offers a promising route to overcome delayed light-off issues in modern high-efficiency engines, providing a precise, controllable method to optimize emission control catalysts. Full article

Fine particulate matter (PM_2.5) can have considerable negative effects on human health. An increasing number of scholars are finding that green space can not only decrease PM_2.5 levels but also exacerbate PM_2.5 levels. Few scholars have provided comprehensive reviews on this subject. This study reviews research from 1995 to 2024, including 118 studies based on a search of three databases (Web of Science, Engineering Village, and ResearchGate). We found that at the macro (e.g., city-wide) and meso (e.g., high-density built-up areas) scales, most studies report that green space can play a positive role in mitigating PM_2.5 concentrations. However, at the micro-scale under specific temporal conditions, green spaces may increase PM_2.5 concentrations in some micro-environments. Whether vegetation reduces or elevates local PM_2.5 levels, these processes are influenced by various factors, including green space configuration, microclimatic conditions, built-environment characteristics, and emission source distributions. Mechanistically, vegetation can both decrease ambient PM_2.5 levels through deposition, adsorption, and absorption and block its dispersion. In the process of exploring and optimizing the effect of greening on PM_2.5, we should not only consider these factors in isolation but also account for the environmental factors that can significantly change the effect. Based on our review of a myriad of studies from different disciplinary backgrounds and scales, we propose an optimization strategy consisting of promoting ventilation through weakening sources and strengthening sinks. Full article

Biomass briquettes are increasingly used as renewable solid fuels, yet their durability under humid storage remains a key limitation. This study evaluated the mechanical performance and water resistance of briquettes made from fine (0–1 mm) and coarse (0–3 mm) charcoal fractions using molasses as a primary binder, polyvinyl alcohol (PVA, 3–7%) as a synthetic binder, and liquid soap (1–9%) as a surfactant additive. Compressive strength was measured in the dry state, after four days of water immersion, and after re-drying, while water absorption was monitored over immersion times from 15 min to 4 days. Fine-fraction briquettes showed higher strength and lower water uptake than coarse fractions, with optimal PVA contents of 6–7% providing maximum dry and post-drying strength. Moderate soap addition (2–3%) improved binder dispersion and early wet strength, whereas higher levels (>5%) reduced durability. Water absorption kinetics indicated that particle size controlled early swelling, while binder composition influenced the rate but not the final saturation. The best performance in humid storage was achieved by 0–1 mm + 4% PVA and 0–1 mm + 5% PVA + 3% soap formulations. These results support the formulation of eco-friendly binder systems that balance strength, moisture resistance, and cost for large-scale biomass briquette production. Full article

Overcoming the strength–ductility trade-off in conventional aluminum matrix composites (AMCs) remains a significant challenge. This study employs dual-scale hybrid reinforcement particles comprising micron-sized Cu and nano-sized Ti, alongside bimodal micro-sized pure Al powders as matrix fillers. The AMCs were fabricated through ball milling (BM) combined with multi-pass friction stir processing (FSP). The homogenously distributed hybrid reinforcement particles generate an integrated composite region consisting of both coarse-grained (CG) and fine-grained (FG) structures, demonstrating enhanced material characteristics. The interwoven network of coarse- and fine-crystalline domains constructs a heterogeneous architecture that enables simultaneous improvement in both strength and ductility properties. The micron-Cu acts as a skeletal support within the matrix, enhancing load transfer efficiency and effectively hindering dislocation motion. The nano-Ti and in situ intermetallics facilitate grain refinement via the pinning effect and promote heterogeneous nucleation, which contributes to stress dispersion and dislocation obstruction. The addition of dual-scale micron-sized pure Al powder particles promotes the formation of the heterogeneous architecture, which enhances the balancing of strength and ductility in the composite. Following compositing (Al₁₀-5Cu-10Ti-10Al₂₀), the alloy exhibits an ultimate tensile strength (UST) of 267 MPa, a hardness of 98 HV, and an elongation of 16.7%, representing increases of 193.4%, 226.7%, and 9.9%, respectively, relative to the base metal. Full article

Al-Zn-Mg-Cu alloys are widely used as heat-treatable ultra-high-strength materials in aerospace structural applications. While conventional single-stage aging enables high strength, advanced performance demands call for precise microstructural control via multi-stage aging. In this study, we employ a combination of scanning transmission electron microscopy (STEM), energy-dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD) to investigate the microstructural evolution and its correlation with mechanical properties of AA7150 aluminum alloy subjected to two-step aging treatments, following a 6 h pre-aging at 120 °C. Through atomic-scale STEM imaging along the [110]_Al zone axis, we systematically characterize the precipitation behavior of GPII zones, η′ phases, and equilibrium η phases both within the grains and at grain boundaries under varying secondary aging (SA) conditions. Our results reveal that increasing the SA temperature from 140 °C to 180 °C leads to coarsening and reduced number density of intragranular precipitates, while promoting the continuous and coarse precipitation of η phases along grain boundaries, accompanied by a widening of the precipitation-free zone (PFZ). Notably, SA at 160 °C induces the formation of fine, uniformly dispersed nanoscale η′ precipitates in the alloy, as confirmed by XRD phase analysis. Aging at this temperature markedly enhances the mechanical properties, achieving an ultimate tensile strength (UTS) of 613 MPa and a yield strength (YS) of 598 MPa, while presenting an exceptionally broad peak-aging plateau. Owing to this feature, a moderate extension of the SA duration does not reduce strength and can further improve ductility, increasing the elongation (EL) to 14.26%. These results demonstrate a novel two-step heat-treatment strategy that simultaneously achieves ultra-high strength and excellent ductility, highlighting the critical role of advanced electron microscopy in elucidating phase-transformation pathways that inform microstructure-guided alloy design and processing. Full article

It is widely recognized that benthic sediment plumes generated by deep-sea mining may pose significant potential risks to ecosystems, yet their dispersion behavior remains difficult to predict with accuracy. In this study, we combined laboratory experiments with three-dimensional numerical simulations using the Environmental Fluid Dynamics Code (EFDC) to investigate the dispersion of sediment plumes composed of particles of different sizes. Laboratory experiments were conducted with deep-sea clay samples from the western Pacific under varying conditions for plume dispersion. Experimental data were used to capture horizontal diffusion and vertical entrainment through a Gaussian plume model, and the results served for parameter calibration in large-scale plume simulations. The results show that ambient current velocity and discharge height are the primary factors regulating plume dispersion distance, particularly for fine particles, while discharge rate and sediment concentration mainly control plume duration and the extent of dispersion in the horizontal direction. Although the duration of a single-source release is short, continuous mining activities may sustain broad dispersion and result in thicker sediment deposits, thereby intensifying ecological risks. This study provides the first comprehensive numerical assessment of deep-sea mining plumes across a range of particle sizes with clay from the western Pacific. The findings establish a mechanistic framework for predicting plume behavior under different operational scenarios and contribute to defining threshold values for discharge-induced plumes based on scientific evidence. By integrating experimental, theoretical, and numerical approaches, this work offers quantitative thresholds that can inform environmentally responsible strategies for deep-sea resource exploitation. Full article

High-precision semantic segmentation of remote sensing imagery is crucial in geospatial analysis. It plays an immeasurable role in fields such as urban governance, environmental monitoring, and natural resource management. However, when confronted with complex objects (such as winding roads and dispersed buildings), existing semantic segmentation methods still suffer from inadequate target recognition capabilities and multi-scale representation issues. This paper proposes a neural network model, LMVMamba (LoRA Multi-scale Vision Mamba), for semantic segmentation of remote sensing images. This model integrates the advantages of convolutional neural networks (CNNs), Transformers, and state-space models (Mamba) with a multi-scale feature fusion strategy. It simultaneously captures global contextual information and fine-grained local features. Specifically, in the encoder stage, the ResT Transformer serves as the backbone network, employing a LoRA fine-tuning strategy to effectively enhance model accuracy by training only the introduced low-rank matrix pairs. The extracted features are then passed to the decoder, where a U-shaped Mamba decoder is designed. In this stage, a Multi-Scale Post-processing Block (MPB) is introduced, consisting of depthwise separable convolutions and residual concatenation. This block effectively extracts multi-scale features and enhances local detail extraction after the VSS block. Additionally, a Local Enhancement and Fusion Attention Module (LAS) is added at the end of each decoder block. LAS integrates the SimAM attention mechanism, further enhancing the model’s multi-scale feature fusion capability and local detail segmentation capability. Through extensive comparative experiments, it was found that LMVMamba achieves superior performance on the OpenEarthMap dataset (mIoU 52.3%, OA 69.8%, mF1: 68.0%) and LoveDA (mIoU 67.9%, OA 80.3%, mF1: 80.5%) datasets. Ablation experiments validated the effectiveness of each module. The final results indicate that this model is highly suitable for high-precision land-cover classification tasks in remote sensing imagery. LMVMamba provides an effective solution for precise semantic segmentation of high-resolution remote sensing imagery. Full article

The present research investigates the fine-scale spatial genetic structure (SGS) and gene flow dynamics in the endangered relict tree Tetracentron sinense, a keystone species in China’s montane ecosystems facing severe habitat fragmentation and genetic erosion. Utilizing genome-wide SNPs from 378 individuals across four natural populations (BMXS, MGFD, GLGS, SXFP), derived from ddRAD-seq, we quantified genetic diversity, SGS (Sp statistic), and dispersal patterns through spatial autocorrelation, parentage analysis, and age-class stratification. Results indicated critically low heterozygosity (observed heterozygosity, H_O = 0.019–0.022) and high inbreeding coefficient (Fis = 0.147–0.304), with moderate SGS (Sp = 0.0076–0.021) suggesting restricted gene flow (effective dispersal radius: 11–32 m). Seed-mediated dispersal was predominant, but topography and rainfall constrained dispersal (<5% beyond 50 m). Saplings exhibited stronger SGS, and the SXFP population experienced 100% sapling mortality due to inbreeding depression. Conservation efforts should prioritize assisted gene flow, habitat restoration, and ex situ sampling at distances greater than 115 m to preserve genetic diversity and adaptive potential. This study highlights the urgent need for genomics-informed conservation strategies in fragmented montane ecosystems. Full article

The present study concentrates on the role and underlying mechanisms of in situ crystallization (employed for nanocrystal formation) in influencing the solidification microstructure and properties of aluminum alloys. By systematically analyzing the effects on α-Al refinement, silicon phase modification, and secondary phase control, as well as exploring the impact on room-temperature mechanical properties, high-temperature deformation behavior, and fatigue performance, this work reveals the potential physical mechanisms of improving mechanical properties by providing nucleation sites and inhibiting grain growth, such as fine-grain strengthening and dispersion strengthening. Moreover, stabilization of the second phase optimizes high-temperature deformation behavior, and a reduction in stress concentration improves fatigue performance. Compared with traditional microstructure control methods, in situ crystallization can achieve deeper grain refinement from micron to nanometer scale, ensuring high uniformity of grain distribution and showing good compatibility with existing processes. By defining the regulation of in situ crystallization on the microstructure and properties of aluminum alloy, the existing research provides a feasible material solution for high stress, high temperature, and high reliability. Its core significance lies in breaking through the performance bottlenecks of traditional modification technology, such as unstable refining effect, element segregation, and so on. The co-promotion of “strength–plasticity–stability” of aluminum alloys and the consideration of process compatibility and cost controllability lay a theoretical and technical foundation for the industrialization of high-performance aluminum alloys. Full article