Search Results (8,404)

In this study, bioceramic composites based on zirconia (ZrO₂) were synthesized and characterized in terms of mechanical properties. Two types of different-sized grains of zirconia powders were used to prepare the composites. A commercial zirconia micropowder (Tosoh) was used as a base for the composites modified with bioactive glass (BG), copper-doped bioactive glass (BGCu), and hexagonal boron nitride (hBN) with a sintering temperature of 1450 °C. The composites with the addition of hydroxyapatite, for which their sintering temperature was 1150 °C, were independently fabricated using a zirconia nanopowder prepared via co-precipitation and hydrothermal methods to achieve high densification and avoid hydroxyapatite decomposition. Mechanical performance of these composites was assessed with regard to biaxial flexural strength, Vickers hardness (HV), and fracture toughness (K_Ic). The reference 3Y-TZP material exhibited Vickers hardness (11.8 GPa) and fracture toughness (6.1 MPa∙m^1/2 values typical for dense tetragonal zirconia ceramics. The addition of all bioactive phases resulted in significant alterations in mechanical properties. Specifically, incorporating 20 wt.% HAp led to a threefold decrease in hardness and a 40% reduction in fracture toughness, while increasing the HAp content to 40 wt.% further reduced these properties. Nonetheless, the fracture toughness of these composites remained higher than that of pure hydroxyapatite materials. The incorporation of BG and BGCu reduced the hardness values by 45% and 30%, respectively, compared to 3Y-TZP. The most significant deterioration of the properties was observed for the 3Y-TZP-hBN composite. The 3Y-TZP–BGCu composite exhibited fracture toughness (5.9 MPa∙m^1/2) representing 95% of the toughness of pure zirconium dioxide, thereby showing the lowest weakness of all the other composites with bioactive additives. A slightly lower fracture toughness value (5.3 MPa∙m^1/2) was also observed in the composite with bioglass but lacking the copper additive. This factor, combined with a relatively small decrease in hardness in both cases, highlights high durability for implantology applications, thus marking the indicated materials the most promising among the composites studied. Full article

To explore the regulatory mechanisms of different vegetation types on soil crust grain-size characteristics in sandy lands, this study focused on five typical plant species (Haloxylon ammodendron, Artemisia ordosica, Nitraria tangutorum, Agriophyllum squarrosum, and Phragmites australis) in an artificial vegetation restoration area on the northeastern edge of the Ulan Buh Desert. Using laser granulometry and graphical methods, we systematically determined the soil particle size composition and parameters of the crust (Layer A) and sub-crust (Layer B) layers, and analyzed their correlations with plant morphological parameters (crown width, plant height, basal diameter). The results showed that (1) different vegetation types significantly increased the content of soil fine particulate matter (silt and clay), with fine sand accounting for 42.85% and silt accounting for 23.64%; (2) there are significant differences in the impact of different vegetation types on particle size parameters. The average particle size of soil crust under Phragmites australis is the smallest (1.91), and the sorting is the worst (standard deviation 2.01). Under the vegetation type of Nitraria tangutorum, the average particle size of the soil crust layer is the largest (5.25), and the fractal dimension is the highest (2.46). (3) The crown width, plant height, and basal diameter of vegetation are negatively correlated with mean particle size, kurtosis, and fractal dimension (r= −0.62 to −0.45), and positively correlated with standard deviation and skewness (r = 0.51 to 0.68). (4) The frequency curve indicates that vegetation types broaden the distribution range of soil particles, and Phragmites australis and Artemisia ordosica exhibit bimodal characteristics. This study reveals the impact of vegetation restoration on soil grain size parameters in arid regions. These findings provide actionable strategies for optimizing vegetation configuration in actual desert restoration projects, notably proposing a “herbs first, shrubs follow” approach that can be directly applied to enhance restoration efficiency. Full article

The research investigates the influence of laser-cladding parameters in WC9 steel-surface multi-track Stellite 12 alloy coatings. Mathematical models of penetration depth, grain size, and microhardness in the coating were developed by Central Composite Design with altering of the input laser power, scanning speed, powder feed rate, and overlapping rate. Response Surface Methodology was used to analyze the correlation of different processing parameters affecting the selected responses. A coating with penetration depth was achieved by significantly reducing the laser power and overlap ratio while increasing the powder feed rate. Appropriately reducing the laser power while increasing the powder feed rate effectively refined the grain size of the Stellite 12 alloy coating. Higher microhardness in the coating was obtained by appropriately increasing the powder feed rate and scanning speed while reducing the laser power. Afterwards, a desired processing parameters set was obtained through optimization with the target of minimizing the penetration depth and grain size and maximizing the microhardness. Experimental validation with this processing parameter setup provided satisfactory coating, and the error rate for the penetration depth, grain size, and microhardness was 9.66%, 7.36%, and 5.46%, respectively. This paper provides the theoretical guidance for the prediction and control of the penetration depth, grain size, and microhardness in WC9 steel-surface multi-track laser cladding with the Stellite 12 alloy. Full article

This study investigates methane leakage and diffusion from a buried high-pressure natural gas pipeline (8 MPa, 1000 mm diameter) using CFD simulations with the DES turbulence model. Based on homogeneous and layered soil models, the influences of soil porosity (0.46 to 0.54), particle size (10 μm to 100 μm), and soil stratification on the spatial and temporal characteristics of methane diffusion are systematically explored. The simulation results show that (1) methane diffuses from the leak hole to the surrounding soil in an ellipsoidal pattern, with the fastest diffusion speed along the pipeline’s axial direction. (2) In homogeneous soil, within the range of soil parameter values considered in this study, the absolute changes in risk assessment indices (FDR, GDR) caused by soil particle size were more significant; whereas the relative percentage changes in risk assessment indicators caused by soil porosity were more pronounced. (3) In layered soil, the permeability contrast between adjacent layers creates the permeability discontinuity interface effect. When a fine-grained or low-porosity layer overlies a coarse-grained layer, the upper layer acts as a hydraulic barrier, prolonging FDT from 130 s to 354 s while promoting significant horizontal spread at the interface. Conversely, a coarse-grained or high-porosity upper layer accelerates vertical breakthrough. These findings provide a scientific basis for risk assessment, monitoring site optimization, and emergency response planning, particularly in regions with heterogeneous stratified soils. Full article

Sandstone-type uranium deposits represent one of the most significant uranium deposit types in China, predominantly hosted in Meso-Cenozoic sedimentary basins in the northern part of the country. Due to characteristics such as deep burial of orebodies, fine grain size of ores, and strong heterogeneity, traditional geological logging methods have limitations in rapidly and accurately identifying alteration minerals and mineralization indicator information. Core spectral technology (wavelength range approximately 400–2500 nm), particularly short-wave infrared spectroscopy (SWIR, 1300–2500 nm), enables rapid, non-destructive, and quantitative extraction of alteration mineral information from drill cores. This provides robust technical support for reconstructing metallogenic environments, delineating oxidation–reduction zones, and prospecting and prediction in sandstone-type uranium deposits. This review systematically examines the spectral absorption characteristics and geological significance of key alteration minerals (e.g., clay minerals, carbonate minerals, iron oxides, and hydrocarbon substances) in sandstone-type uranium deposits. It elaborates on the current application status of core spectral technology in sandstone-type uranium exploration within typical basins in northern China, such as the Ordos, Songliao, Erlian, and Qaidam Basins. These applications include alteration mineral mapping, oxidation–reduction zone delineation, and metallogenic fluid tracing. Due to the unique characteristics of host rock lithology, alteration mineral assemblages, and fluid properties in sandstone-type uranium deposits, the application of this technology also faces certain challenges, such as difficulties in spectral interpretation and insufficient accuracy in quantitative inversion. Integrating this technique with multiple methods, including petrography and X-ray diffraction (XRD), will facilitate more effective applications in both metallogenic research and prospecting practices for sandstone-type uranium deposits in northern China. Full article

Dynamic recrystallization processes are known to significantly affect both the mechanical properties and the microstructure of materials. In this paper, we investigate the influence of discontinuous dynamic recrystallization (dDRX) during deformation at high strain rates (from 10⁴ to 10⁵ s⁻¹) and elevated temperatures in pure aluminum and copper (in the range of 700–800 K for aluminum and 800–1100 K for copper). For this purpose, we propose a theoretical model in which the material is described within the framework of continuum mechanics, plastic deformations are modeled using a dislocation plasticity approach, the equation of state is represented by a neural network, and the microstructure evolution is simulated using the cellular automata method. The model is applied to uniaxial compression and tension of copper and aluminum polycrystals with an initial average grain size of 14 μm. It is shown that grain refinement occurs in all systems. The average grain size decreases from 14 μm to 4–5 μm. The distribution of plastic and total strains in the polycrystals is presented. In all considered systems, deformation localization is observed, and the localization pattern changes due to the nucleation of new grains and grain boundary surfaces during dynamic recrystallization. Full article

In this study, scanning electron microscopy (SEM) analysis is used to reveal the real microstructure of C75S steel and to compare grain morphology and deformation features with numerical predictions. A micro-scale finite element model of C75S steel is developed to investigate its tensile response in order to understand how steel actually deforms and fails at the microstructure level. Subsequently, the validated microstructural model is employed to simulate the cutting process using the finite element method, focusing on stress concentration and damage initiation at the grain and interface zones. The results demonstrate that microstructural modelling provides improved insight into deformation and fracture mechanisms compared to homogenised approaches, highlighting the critical role of cementite distribution and interfacial behaviour during tensile loading and micro-scale cutting. The cementite particle sizes in C75S steel range from approximately 0.5 to 2.0 µm, with circularity values between 0.7 and 0.95 and a volume fraction of about 10–12%. The proposed framework offers a robust basis for predicting the cutting performance of high-carbon steels. Full article

We analyse pebble RFID tracing observations to investigate sediment transport dynamics in gravel-bed rivers using statistical modelling. This study examines a dataset of nearly 3500 tracer displacement measurements collected during 27 sediment-mobilizing events in a pre-Alpine reach in Italy. Our analysis follows three main steps, addressing tracer mobility patterns, event-scale transport dynamics, and reach-scale bedload inference. First, using Markov Chain analysis of state transitions on typical and high-magnitude transport events, we demonstrate that pebbles tend to maintain their mobility state between events, characterizing the between-event intermittency of bedload transport. A subsequent analysis of flow characteristics reveals that consecutive floods of similar magnitude exhibit increasing movement probability while maintaining similar virtual velocities. Finally, we train Gradient Boosting regression models to estimate distributions of pebble displacements and virtual velocities (defined, following common usage, as the ratio between the distance a tracer travels during a mobilising event and the duration of that event). Together with Monte Carlo propagation, these models are used to derive reach-scale volume estimates. The models identify flow rate and event duration as primary controls, while grain size has minimal influence within the sampled range of tracer dimensions. To strengthen our approach, we implement an extensive multi-stage validation process aimed at both single-tracer predictions and overall basin-scale movement estimates. The results indicate that high-magnitude transport events (12% of observations) contribute similar bedload volumes as typical events (88% of observations), highlighting the significant role of extreme events in total sediment transport. Model predictions yield bedload volume estimates that align well with independent measurements from a downstream sediment retention basin. Full article

The thermal conductivity (λ) of porous rocks as a function of total porosity, grain size, and fluid saturation is measured and modeled by combining high-precision experiments with a Staged Differential Effective Medium (SDEM) modeling framework. A 1-D divided-bar apparatus with computer-controlled guard heaters with an integrated ultrasonic pulse-transmission system was developed to measure the thermal conductivity and P and S-wave velocities simultaneously. Measurements were made on Fontainebleau sandstone cores and quartz sand packs of varying grain size and effective stresses up to 2000 psi. The sample properties were measured in both dry and water-saturated states. The SDEM model performs significantly better at predicting the saturated thermal conductivities in the sand packs. For the sand packs, the thermal conductivity and compressional velocity are the highest and most stress-sensitive for the fine-grained material. In contrast, the shear velocity is largest in the coarse-grained material. The SDEM model is adapted from previous acoustic models for use in understanding thermal conductivity. These joint models accurately reproduce the evolution of both thermal conductivity and bulk modulus during increasing compaction and varying saturation. A single parameter fits both the dry and saturated data, which allows Gassmann-style fluid substitution for the thermal conductivity. This model improves the prediction of in situ thermal conductivity from sonic well logs. Full article

In this study, the sintering behavior and electrical properties of 0.7Pb(Zr_0.46Ti_0.54)O₃ (PZT)–0.1Pb(Zn₁/₃Nb₂/₃)O₃ (PZN)–0.2Pb(Ni₁/₃Nb₂/₃)O₃ (PNN) piezoelectric ceramics with different Pb(Fe₂/₃W₁/₃)O₃ (PFW) doping contents were investigated to obtain a formulation that can be co-fired with silver (Ag) electrodes below 900 °C for multilayer ceramics. PFW was introduced as a sintering aid, which effectively reduced the sintering temperature of the ceramics from 1200 °C to 850 °C. The sample with x = 0.12 exhibited the largest average grain size of 1.72 μm, achieving excellent comprehensive properties with piezoelectric constant (d₃₃) = 477 pC/N, planar electromechanical coupling factor (k_p) = 0.68, dielectric loss tangent (tanδ) = 0.0154, and relative density of 98.2%. Furthermore, the feasibility of fabricating piezoelectric actuators based on this optimized composition was verified. Multilayer piezoelectric devices were prepared via screen printing combined with a carbon-based sacrificial layer method. No obvious interdiffusion was observed at the interface between the Ag internal electrodes and the ceramic matrix. The 9-layer device attained a high d₃₃ = 1470 pC/N and produced a large displacement of 5.5 μm (corresponding to a strain = 1.83%) with a voltage of 500 V. The thickness of the multilayer piezoelectric film was approximately 0.3 mm. Through this, the feasibility of manufacturing a multilayered actuator with an Ag electrode was confirmed through the composition of 0.58PZT–0.1PZN–0.2PNN–0.12PFW. Full article

Geopolymer concretes are increasingly regarded as advanced construction materials for applications requiring high thermal and chemical resistance. This article is a continuation of previously published research and focuses on the mechanical behaviour of geopolymer concretes containing aggregates made of foamed geopolymers and lightweight mineral aggregates, such as expanded clay and perlite, intended for use in chimney flue components. The aim of the study was to determine the influence of lightweight aggregates on the relationship between thermal insulation and the strength parameters of geopolymer concretes intended for use at elevated temperatures. Foamed geopolymer aggregates were produced by a controlled chemical foaming process, followed by grinding to specific grain sizes, yielding highly porous aggregates with low thermal conductivity, reaching approximately 0.075–0.099 W/(m·K). These aggregates were used as lightweight fillers in geopolymer concretes based on class F fly ash activated with alkaline solutions. The resulting composites were designed to combine low density and high thermal insulation with adequate mechanical strength. The mechanical properties of the developed concretes were assessed on the basis of compressive strength tests on cubic specimens and tensile strength in beam bending tests, carried out in accordance with standards. The results presented confirm that the use of foamed geopolymer aggregates enables a simultaneous increase in thermal insulation and the design of ultra-lightweight structural elements with sufficient load-bearing capacity for chimney systems (including suspended ones). This combination of low thermal conductivity, reduced mass, and appropriate mechanical properties makes geopolymer concretes with lightweight mineral and geopolymer aggregates a promising alternative to traditional ceramic materials. Full article

Recently, a substantial quantity of oil and gas has been discovered in the pre-salt Lower Cretaceous microbialite successions of Brazil’s Santos Basin, thereby prompting a global surge in research related to microbialites. It has been demonstrated that microbial shoal reservoirs yield the highest hydrocarbon production, with optimal reservoir properties, as evidenced by experience in the field of oilfield production. However, as research progresses, it has become increasingly evident that significant heterogeneity exists in both the lithology and physical properties within microbial shoal bodies. In order to address the identified knowledge gap, the present study employs systematic petrological and petrophysical datasets. These include 30-m continuous core samples, thin-section analyses, routine petrophysical tests and mercury injection capillary pressure (MICP) measurements. The aim is to characterize the internal microfacies architecture and reservoir heterogeneity of microbial shoals. It is imperative to ascertain the principal factors that govern the heterogeneity observed in these reservoirs. This critical step is essential for a comprehensive understanding of the subject matter. The results of the study demonstrate that: the Barra Velha Formation microbial shoals in the Santos Basin can be subdivided into three microfacies, which are delineated from base to top. The foundation of the shoal is the shoal base. The rock composition is dominated by the presence of spherulites, with intracrystalline pores functioning as the primary reservoir spaces. The compositional rocks of the shoal flank are poorly sorted microbial debris, with intergranular and intragranular pores formed by penecontemporaneous dissolution. The sedimentary succession of the shoal core is characterized by well-sorted microbial debris rocks displaying multiple shallowing-upward sequences, with reverse-graded textures. The primary storage space is constituted by fabric-selective pores from penecontemporaneous dissolution, though these are subject to local disruption by destructive silicification. Meanwhile, the microbial shoals demonstrate wide porosity (8.8–26.4%, mean 16.8%) and permeability (0.13–839 mD, mean 169 mD) ranges, thus classifying them as medium-porosity, high-permeability reservoirs. The superimposition of microfacies and diagenetic processes gives rise to considerable reservoir heterogeneity. It is evident that the shoal core microfacies exhibits robust energy and substantial grain size, characteristics that facilitate its exposure above lake level during periods of high-frequency lake-level oscillation. This exposure is further compounded by the influence of atmospheric water dissolution, which remodels the microfacies during the quasi-contemporaneous period. The reservoir quality is optimal, exhibiting the highest proportion of large pores. The reservoir properties of the shoal flank are closely followed by medium and large pores, and those of the shoal base are the worst, with micro and medium pores. Full article

This study systematically investigates the effects of solution temperature ranging from 1060 to 1150 °C on grain growth kinetics, microstructural evolution, and tensile properties of GH4698 superalloys. The results indicate that grain size coarsens parabolically with increasing solution temperature. Based on the Sellars model, the grain growth time exponent n is determined to be 3.4 and the activation energy Q is 478.7 kJ·mol⁻¹. This confirms that the grain growth process is significantly influenced by both MC carbide pinning and alloying element drag effects. Additionally, due to the coarsening of grains, the precipitation density of M₂₃C₆ carbides per unit grain boundary length increased from 0.26 μm⁻¹ to 0.39 μm⁻¹. The ultimate tensile strength at room temperature decreased from 1268 MPa to 1226 MPa, and the yield strength decreased from 840 MPa to 807 MPa, while the elongation remained at 28–32%. At 700 °C, the ultimate tensile strength decreases from 974 MPa to 904 MPa, and the yield strength decreases from 755 MPa to 696 MPa, with the elongation remaining at ~6%. Quantitative analysis reveals that the decrease in strength is primarily due to the weakening of grain boundary strengthening caused by grain coarsening. At 700 °C, the deformation mechanism transitions from dislocation shearing at room temperature to stacking fault shearing. This not only leads to a reduction in strength but also, accompanied by grain boundary weakening, results in a decrease in elongation. Full article

Foliar preparations are used in potato cultivation, and their use can affect starch properties, which are important for food production. Therefore, the aim of this study was to evaluate the effect of foliar application of preparations (biostimulants, fertilizers) during the growing season of potatoes (Solanum tuberosum L.), cultivar Concordia, on selected physicochemical, thermal, and rheological properties of starch. Eight commercial preparations (Basfoliar 12-4-6+S + ADOB PK (ADOB), Asahi SL, BlueN^®, Megafol^®, Quantis™, Qultivo, Rizoderma TSI, and Rizofos) were foliarly applied during the growing season. Potato starch was isolated using a laboratory method. Starch from potatoes grown without foliarly preparations served as a control sample. The research methodology included determination of amylose content and mean starch granule diameter. Thermodynamic characterization of gelatinization and retrogradation was performed using a DSC (differential scanning calorimeter), viscometric pasting characterization was performed with a Rapid Visco Analyzer (RVA), and flow curves were determined. A statistically significant effect of the type of foliar biostimulant/fertilizer applied on amylose content, starch grain size distribution, and rheological properties of the tested starches was observed. Amylose content ranged from 31.7% (BlueN) to 36.3% (ADOB). Starch from potatoes grown with ADOB had the largest grains, with the largest number of grains having a diameter >40 µm. The tested starches generally did not differ in terms of the onset, peak, and end temperatures of gelatinization determined using DSC. Similarly, slight differences were observed in the pasting temperature determined viscometrically. The RVA analysis showed that the highest maximum viscosity value was observed for starch obtained from the raw material stimulated with the Megafol preparation (3744 mPa·s), and the paste based on starch isolated from potatoes grown with the Asahi biostimulant was characterized by the highest rheological stability at 95 °C. The starch pastes obtained from the raw material stimulated with the Megafol and Quantis preparations were characterized by the lowest values of the consistency coefficient (15.7 Pa·sⁿ), and the control starch had the highest value of this parameter (21.7 Pa·sⁿ). Full article

Online and blended classrooms widen access but remove the in-person cues instructors use to gauge attention. Prior work typically relies on heavy, cloud-bound or multimodal models that are hard to deploy on commodity laptops, treats attention as an unordered label without calibrated probabilities, and evaluates on subject-overlapping splits with limited robustness analysis. This creates a gap in Tiny, deployable, calibration-aware methods validated under realistic protocols. We address this gap with a TinyML, vision-only pipeline that estimates four attention levels: (Very Low, low, high, Very High ) from short webcam clips under strict on-device budgets. Each clip of $T=30$ frames at $224\times 224$ is processed by a compact hybrid encoder: a CNN extracts per frame spatial features, a BiLSTM models temporal context, and a lightweight GRU refines dynamics; three parallel branches with staggered widths encourage feature diversity before fusion. We apply structured pruning of convolutional channels and recurrent units, post-training INT8 quantization, and temperature scaling for calibrated probabilities; models are exported as ONNX. On DAiSEE with subject-independent splits, the baseline attains $99.86\%$ accuracy and $0.998$ macro-F1, with strong ordinal agreement (QWK = 0.998, ordinal MAE = 0.03). The compressed model preserves reliability (macro-F1 = 0.995, QWK = 0.995), remains robust to low light, partial occlusion, and head yaw, and yields ∼4× smaller size and ∼2.3× CPU speedups. These results indicate a deployable, privacy-preserving approach to fine-grained, on-device attention analytics. Full article