Search Results (774)

Surface and sub-surface atomic configurations are critical for catalysis as they host the active sites governing electrochemical processes. This study employs density functional theory (DFT) calculations and Monte Carlo simulations combined with the cluster-expansion approach to investigate atom distribution and Pt segregation in Pt-Fe alloys across varying Pt/Fe ratios. Our simulations reveal a strong tendency for Pt atoms to segregate to the surface layer while Fe atoms enrich the sub-surface region. Crucially, the calculations predict the stability of a periodic Pt₂Fe alloy surface model, characterized by specific defect structures, at low platinum content and low annealing temperatures. Electronic structure analysis indicates that forming this Pt₂Fe surface alloy lowers the d-band center of Pt atoms, weakening CO adsorption and thereby enhancing resistance to CO poisoning. Although defect-induced strains can modulate the d-band center, crystal orbital Hamilton population (COHP) analysis confirms that such strains generally strengthen Pt-CO interactions. Therefore, the theoretical design of Pt₂Fe alloy surfaces and controlling defect density are predicted to be effective strategies for enhancing catalyst resistance to CO poisoning. This work highlights the advantages of periodic Pt₂Fe surface models for anti-CO poisoning and provides computational guidance for designing efficient Pt-based electrocatalysts. Full article

Mozambique soils are known for having an unbalanced agronomic and environmental composition that results in poor agricultural production yields. However, agriculture is the main economic activity of Mozambique, and soils must be characterised for their elemental deficiencies and/or excesses. This paper sampled nine farms from the Manica and Sussundenga districts (Manica province) in three campaigns in 2021/2022, 2022/2023, and 2023/2024 (before and after the rainy seasons). They were subjected to a physical–chemical analysis to assess their quality from the fertility and environmental contamination point of view. Attending to the physical–chemical properties analysed, and for all the soils and sampling campaigns, a low concentration below the limit of detection for B of <0.2 mg/Kg for the majority of soils and a low concentration of Al < 0.025 mg/Kg for all the soils were obtained. Also, higher concentrations for the majority of soils for the Ca between 270 and 1634 mg/Kg, for the Mg between 41 and 601 mg/Kg, for the K between 17 and 406 mg/Kg, for the Mn between 13.6 and 522 mg/Kg, for the Fe between 66.3 and 243 mg/Kg, and for the P between <20 and 132 mg/Kg were estimated. In terms of texture and for the sand, a high percentage between 6.1 and 79% was found. In terms of metal concentrations and for all the soils of the Sussundenga district and sampling campaigns, a concentration above the reference value concentration for the Cr (76–1400 mg/Kg) and a concentration below the reference value concentration for the Pb (5–19 mg/Kg), Ba (13–120 mg/Kg) and for the Zn (10–61 mg/Kg) were evaluated. A multivariate data analysis methodology was used based on cluster and discriminant analysis. The analysis of twenty-three physical–chemical variables of the soils suggested four clusters of soils characterised by deficiencies and excess elements that must be corrected to improve the yield and quality of agricultural production. Moreover, the multivariate analysis of the metal composition of soil samples from the second and third campaigns, before and after the rainy season, suggested five clusters with a pristine composition and different metal pollutant compositions and concentrations. The information obtained in this study allows for the scientific comprehension of agricultural soil quality, which is crucial for designing agronomic and environmental corrective measures to improve food quality and quantity in the Manica and Sussundenga districts and ensure environmental, social, and economic sustainability. Full article

The Ichubamba Yasepan wetlands, in the Andean páramos of Ecuador, suffer heavy metal contamination due to anthropogenic activities and volcanic ash from Sangay, impacting biodiversity and ecosystem services. This quasi-experimental study evaluated the bioaccumulation and tolerance of metals in high Andean species through stratified random sampling and linear transects in two altitudinal ranges. Concentrations of Cr, Pb, Hg, As, and Fe in water and the tissues of eight dominant plant species were analyzed using atomic absorption spectrophotometry, calculating bioaccumulation indices (BAIs) and applying principal component analysis (PCA), clustering, and linear discriminant analysis (LDA). Twenty-five species from 14 families were identified, predominantly Poaceae and Cyperaceae, with Calamagrostis intermedia as the most relevant (IVI = 12.74). The water exceeded regulatory limits for As, Cr, Fe, and Pb, indicating severe contamination. Carex bonplandii showed a high BAI for Cr (47.8), Taraxacum officinale and Plantago australis for Pb, and Lachemilla orbiculata for Hg, while Fe was widely accumulated. The LDA highlighted differences based on As and Pb, suggesting physiological adaptations. Pollution threatens biodiversity and human health, but C. bonplandii and L. orbiculata have phytoremediation potential. Full article

The present work was performed in greenhouse conditions, and 10 ppm Se, 10 ppm B, and 100 mM salinity treatments were used. The results showed significant variations in the agronomic traits of oregano among the treatments and harvests. The 10 ppm Se×10 ppm B treatment showed improvements over other properties for morphological and yield properties with protein, essential oil, and Zn contents, and B×salinity outperformed other treatments, with variations in branch number enhancement. The analysis revealed that salinity treatment could effectively enhance Na and Ca contents. B treatment significantly improved Mn (12,443.51–18,739.77 ppm), Mg (406.85–632.79 ppm), Fe (61.43–885.06 ppm), Cu (5.02–9.32 ppm), and B (37.67–114.28 ppm) element contents. The highest K content was found from Se treatment. The effects of the Se, B, and salinity treatments showed effectively after second and third harvests of the oregano for the many examined properties. Fresh and dry weight values showed variability between 1.60–6.00 g/plant and 0.54–2.42 g/plant, respectively. Principal coordinate analysis indicated that most of the properties took place in the groups 1 (1st harvests of plant height and protein content, 2nd harvests of protein content and fresh and dry weight, 3rd harvest of fresh weight and total fresh and dry weight values) and 2 (branch number and essential oil contents, Na, and Zn). The heat-map analysis divided into two main clusters as A and B. A2, A4, and A5 treatments took place in the B group. Treatment of 10 ppm Se×10 ppm B showed better values compared to other treatments. Thus, this treatment may be beneficial for oregano cultivation under non-saline conditions. Full article

Soil quality assessment plays a critical role in promoting sustainable land management, particularly in fragile steppe ecosystems. This study provides a comprehensive geoecological evaluation of heavy metal contamination (Pb, Cd, Zn, Cu, Co, Ni, Fe, and Mn) in soils across five districts of the Akmola region, Kazakhstan. The assessment incorporates multiple integrated pollution indices, including the geochemical pollution index (Igeo), pollution coefficient (CF), ecological risk index (Er), pollution load index (PLI), and integrated pollution index (Zc). Spatial analysis combined with multivariate statistical techniques (PCA and clustering analysis) was used to identify pollutant distribution patterns and differentiate areas by risk levels. The findings reveal generally low to moderate contamination, with cadmium (Cd) posing the highest environmental risk due to its elevated toxic response coefficient, despite its low concentration. The study also explores the connection between current soil conditions and historical land-use changes, particularly those associated with the Virgin Lands Campaign of the mid-20th century. The highest PLI values were recorded in the Yesil and Atbasar districts (7.88 and 7.54, respectively), likely driven by intensive agricultural activity and lithological factors. PCA and cluster analysis revealed distinct spatial groupings, reflecting heterogeneity in both the sources and distribution of soil pollutants. Full article

Sternal bursitis is an underexplored lesion in poultry, often overlooked in microbiological diagnostics. In this study, we characterized 36 Escherichia coli isolates recovered from sternal bursitis in broiler chickens, combining phenotypic antimicrobial susceptibility testing, PCR-based screening, and whole genome sequencing (WGS). The genetic analysis revealed a diverse population spanning 15 sequence types, including ST155, ST201, and ST58. Resistance to tetracycline and ciprofloxacin was common, and several isolates carried genes encoding β-lactamases, including blaTEM-1B. Chromosomal mutations associated with quinolone and fosfomycin resistance (e.g., gyrA p.S83L, glpT_E448K) were also identified. WGS revealed a high number of virulence-associated genes per isolate (58–96), notably those linked to adhesion (fim, ecp clusters), secretion systems (T6SS), and iron acquisition (ent, fep, fes), suggesting strong pathogenic potential. Many isolates harbored virulence markers typical of ExPEC/APEC, such as iss, ompT, and traT, even in the absence of multidrug resistance. Our findings suggest that E. coli from sternal bursitis may act as reservoirs of resistance and virulence traits relevant to animal and public health. This highlights the need for including such lesions in genomic surveillance programs and reinforces the importance of integrated One Health approaches. Full article

Shale and coal in the transitional marine–continental facies of the Ordos Basin serve as unconventional natural gas reservoirs, with their pore structures controlling gas adsorption characteristics and occurrence states. To quantitatively characterize the pore structure features and differences between these two reservoirs, this study takes the Shanxi Formation shale and coal in the Daning–Jixian area on the eastern margin of the Ordos Basin as examples. Field-emission scanning electron microscopy (FE-SEM), high-pressure mercury intrusion, low-temperature N₂ adsorption, and low-pressure CO₂ adsorption experiments were employed to analyze and compare the full-scale pore structures of the shale and coal reservoirs. Combined with methane isothermal adsorption experiments, the gas adsorption capacity and its differences in these reservoirs were investigated. The results indicate that the average total organic carbon (TOC) content of shale is 2.66%, with well-developed organic pores, inorganic pores, and microfractures. Organic pores are the most common, typically occurring densely and in clusters. The average TOC content of coal is 74.22%, with organic gas pores being the dominant pore type, significantly larger in diameter than those in transitional marine–continental facies shale and marine shale. In coal, micropores contribute the most to pore volume, while mesopores and macropores contribute less. In shale, mesopores dominate, followed by micropores, with macropores being underdeveloped. Both coal and shale exhibit a high SSA primarily contributed by micropores, with organic matter serving as the material basis for micropore development. The methane adsorption capacity of coal is 8–29 times higher than that of shale. Coal contains abundant organic micropores, providing a large SSA and numerous adsorption sites for methane, facilitating gas adsorption and storage. This study comprehensively reveals the similarities and differences in pore structures between transitional marine–continental facies shale and coal reservoirs in the Ordos Basin at the microscale, providing a scientific basis for the precise evaluation and development of unconventional oil and gas resources. Full article

European integration aims to achieve spatially sustainable development across the member states. However, the success of socio-economic integration is conditioned by structural features of the economies, which, hitherto, appear highly diversified across the EU countries. The paper focuses on the structural conditions of the process of income inequality convergence. It aims to identify differences in the convergence regarding the structural conditions of the economies. To fulfil the research tasks the paper classifies the 27 European member states according to their sectional employment structures using the Ward method. It then tests the appearance of beta convergence using FE panel models for the specified clusters of economies. It also considers structural change, measured by the NAV (norm of absolute value), as a determinant of income inequality convergence. The main research period covers 2009–2021. The findings of the paper confirm that income inequality convergence occurs within the groups of economies specified by different structural conditions. Importantly, the clustering according to the similarity of the employment structure overlaps with the division along the lines of the ‘new’ and ‘old’ member states, which proves the importance of historically shaped institutions for development. However, the observed convergence does not lead to improved social cohesion. Social policy, especially in the ‘new’ member states, is not able to offset the growth in market income inequality additionally stimulated by the structural changes. It can be concluded that an urgent need to design new solutions for social policy concerning structural transformation in employment in the EU emerges. Full article

Digital twin models utilising point cloud data have received significant attention for efficient bridge maintenance and performance assessment. There are some studies that show finite element (FE) models from point cloud data. While most of those approaches focus on modelling by solid elements, modelling of some civil structures, such as bridges, requires various uses of beam and shell elements. This study proposes a systematic approach for constructing shell element FE models from point cloud data of thin-walled structural members. The proposed methodology involves k-means clustering for point cloud segmentation into individual plates, principal component analysis for neutral plane estimation, and edge detection based on normal vector variations for geometric structure determination. Validation experiments using point cloud data of a steel corner specimen revealed dimensional errors up to 5 mm and angular errors up to 6°, but static load analysis demonstrated good accuracy with maximum displacement errors within 3.8% and maximum stress errors within 7.7% compared to nominal models. Additionally, the influence of point cloud data quality on FE model geometry and analysis results was evaluated based on geometric accuracy and point cloud density metrics, revealing that significant variations in density within the same surface lead to reduced neutral plane estimation accuracy. Furthermore, toward practical application to actual bridge structures, on-site measurements and quality evaluation of point cloud data from a steel plate girder bridge were conducted. The results showed that thickness errors in the bridge data reached up to 2 mm, while surface deviation RMSE ranged from 3 to 5 mm. This research contributes to establishing practical FE modelling procedures from point cloud data and providing a model validation framework that ensures appropriate abstraction in structural analysis. Full article

Heavy metal contamination in groundwater has emerged as a significant environmental issue, driven by rapid industrialization and intensified human activities, particularly in southern China. Heavy metal pollution in groundwater often presents complex spatial patterns and multiple sources; understanding the spatial heterogeneity and controlling factors of heavy metals is crucial for pollution prevention and water resource management in industrial regions. This study applied spatial autocorrelation analysis and self-organizing maps (SOM) coupled with K-means clustering to investigate the spatial distribution and key influencing factors of nine heavy metals (Cr, Fe, Mn, Ni, Cu, Zn, As, Ba, and Pb) in a typical industrial area in southern China. Heavy metals show significant spatial heterogeneity in concentrations. Cr, Mn, Fe, and Cu form local hotspots near urban and peripheral zones; Ni and As present downstream enrichment along the river pathway with longitudinal increase trends; Zn, Ba, and Pb exhibit a fluctuating pattern from west to east in the piedmont region. Local Moran’s I analysis further revealed spatial clustering in the northwest, riverine zones, and coastal outlet areas, providing insight into potential source regions. SOM clustering identified three types of groundwater: Cluster 1 (characterized by Cr, Mn, Fe, and Ni) is primarily influenced by industrial pollution and present spatially scattered distribution; Cluster 2 (dominated by As, NO₃⁻, Ca²⁺, and K⁺) is associated with domestic sewage and distributes following river flow; Cluster 3 (enriched in Zn, Ba, Pb, and NO₃⁻) is shaped by agricultural activities and natural mineral dissolution, with a lateral distribution along the piedmont zone. The findings of this study provide a scientific foundation for groundwater pollution prevention and environmental management in industrialized areas. Full article

In this study, an innovative dental functionalized magnetic nanomaterial was developed by incorporating hydrophilic magnetic clusters as an alternative to conventional isolated magnetic nanoparticles, introducing a novel structural and functional concept in dental applications. The ~100 nm magnetic clusters—composed of densely packed 7 nm Fe₃O₄ nanoparticles—were sequentially coated with a silica (SiO₂) layer (3–5 nm) to improve chemical and mechanical stability, followed by an outer calcium hydroxide [Ca(OH)₂] layer to enhance bioactivity and optical integration. This bilayer architecture enables magnetic field-assisted positioning and improved dispersion within dental resin matrices. Silver nanoparticles were incorporated to enhance antimicrobial activity and reduce biofilm formation. The synthesis process was environmentally friendly and scalable. Comprehensive physicochemical characterization confirmed the material’s functional performance. Saturation magnetization decreased progressively with surface functionalization, from 62 to 14 emu/g, while the zeta potential became increasingly negative (from −2.42 to −22.5 mV), supporting its ability to promote apatite nucleation. The thermal conductivity (0.527 W/m·K) closely matched that of human dentin (0.44 W/m·K), and the colorimetric analysis showed improved brightness (ΔL = 5.3) and good color compatibility (ΔE = 11.76). These results indicate that the functionalized magnetic nanomaterial meets essential criteria for restorative use and holds strong potential for future clinical applications. Full article

A vital step for any hydrochemical assessment is properly carrying out quality assurance and quality control (QA/QC) techniques to evaluate data confidence before performing the assessment. Understanding the processes governing groundwater evolution in coastal aquifers is critical for managing freshwater resources under increasing anthropogenic and climatic pressures. This study reassesses the hydrochemical and isotopic data from the Deep Confined Aquifer System (DCAS) in the Jiangsu Coastal Plain, China, by firstly applying QA/QC protocols. Anomalously high Fe and Mn concentrations in several samples were identified and excluded, yielding a refined dataset that enabled a more accurate interpretation of hydrogeochemical processes. Using hierarchical cluster analysis (HCA), principal component analysis (PCA), and stable and radioactive isotope data (δ²H, δ¹⁸O, ³H, and ¹⁴C), we identify three dominant drivers of groundwater evolution: water–rock interaction, evaporation, and seawater intrusion. In contrast to earlier interpretations, we present clear evidence of active seawater intrusion into the DCAS, supported by salinity patterns, isotopic signatures, and local hydrodynamics. Furthermore, inconsistencies between tritium- and radiocarbon-derived residence times—modern recharge indicated by ³H versus Pleistocene ages from ¹⁴C—highlight the unreliability of previous paleoclimatic reconstructions based on unvalidated datasets. These findings underscore the crucial role of robust QA/QC and integrated tracer analysis in groundwater studies. Full article

FeCrAl alloys have garnered considerable attention as candidate cladding materials for light water reactors due to their promising mechanical stability and irradiation resistance. However, the response characteristics of these alloys to irradiation and the associated mechanisms remain poorly understood. This study provides atomistic insights into irradiation-induced defect formation and microstructural evolution in polycrystalline FeCrAl. Using the LAMMPS molecular dynamics code, displacement cascades were simulated under irradiation doses ranging from 0.05 dpa to 0.5 dpa while evaluating the dependencies on temperature and grain size. The interaction between pre-existing defects and irradiation-induced microstructures (point defects, dislocations, clusters, etc.) was visualized and analyzed visually and quantitatively. The results indicate that the irradiation dose increases the number of surviving Frenkel pairs, whereas elevated temperatures reduce their stability. The cluster fraction of interstitials increases with both irradiation dose and temperature, while that of vacancies decreases at higher temperatures due to their lower stability. In the initial phase of the displacement cascade, the density and distribution of dislocations evolve continuously until the annealing stage. The dislocation density at the end of the annealing phase decreases with increasing dose and temperature. The thickness of grain boundaries increases with the irradiation dose, and the regions adjacent to grain boundaries transform into an amorphous state at higher dose levels. As both the irradiation dose and temperature increase, the amorphization process accelerates, and smaller grain size leads to a greater degree of amorphization. Full article

Electroless silver (Ag) plating has emerged as a simple yet effective surface modification technique, garnering significant attention in consumer electronics and composite materials. This study systematically investigates the influence of glucose dosage on the microstructural refinement of Ag coatings deposited from silver–ammonia solutions onto iron (Fe) particles while also evaluating the oxidation resistance of Ag-plated particles through thermogravimetric analysis. Optimal results were achieved at a silver nitrate concentration of 0.02 mol/L and a glucose concentration of 0.05 mol/L, producing Fe particles with a uniform and dense silver coating featuring an average Ag grain size of 76 nm. The moderate excess glucose played a dual role: facilitating Ag⁺ ion reduction while simultaneously inhibiting the growth of Ag atomic clusters, thereby ensuring microstructural refinement of the silver layer. Notably, the Ag-plated particles demonstrated superior oxidation resistance compared to their uncoated counterparts. These findings highlight the significance of fine-grained electroless Ag plating in developing high-temperature conductive metal particles and optimizing interfacial structures in composite materials. Full article

Chitin deacetylase (CDA) plays a pivotal role in converting chitin to chitosan, yet industrial applications remain constrained by low enzymatic activity, instability under process conditions, and insufficient understanding of metalloenzyme activation mechanisms. Addressing these challenges, we conducted a genome-driven investigation of 151 salt-tolerant Bacillus strains to identify robust CDAs tailored for industrial demands. Genomic analysis revealed 120 strains harboring CDA genes, with Bacillus pumilus B866 exhibiting the highest native activity (105.93 U/mL). Through systematic medium optimization—identifying lactose, yeast extract, and FeSO₄ as critical components—CDA production in B866 surged to 191.32 U/mL, a 2.39-fold increase over baseline. Heterologous expression of BpCDA in E. coli yielded a recombinant enzyme (123.27 U/mL) with superior thermostability (retaining > 42.9% activity after 24 h at 55 °C) and broad pH adaptability (>81.4% activity at pH 7.0–9.0). Notably, BpCDA demonstrated unique Fe²⁺-dependent activation (186.4% activity enhancement at 1 mM), contrasting with Mg²⁺-dependent systems in prior studies. Comparative genomic and pan-genome analyses underscored evolutionary adaptations linked to saline–alkaline niches, while biosynthetic gene cluster profiling revealed strain-specific metabolic potentials independent of genome size. This study resolves critical limitations in CDA performance by integrating genome mining, targeted screening, and metalloenzyme engineering, establishing a scalable platform for sustainable chitin valorization. The optimized BpCDA, with its industrial-compatible stability and novel activation mechanism, represents a significant advancement toward efficient, eco-friendly chitosan production. Full article