Search Results (548)

This study establishes a robust small-angle neutron scattering (SANS) methodology for the quantitative characterization of γ matrix channel widths in the nickel-based single-crystal superalloy DD10. By combining SANS with TEM analyses and modeling the one-dimensional SANS data via a polydisperse lamellar model, we accurately determined the channel width distribution across macroscopic sample volumes. In the virgin state, the mean channel widths were nearly isotropic, measuring 17.8 ± 0.1 nm along [002] and 20.5 ± 0.1 nm along [020]. After standard heat treatment (solution and two-step aging), significant anisotropic coarsening was observed, with widths increasing to 36.8 ± 0.2 nm along [002] and 28.0 ± 0.1 nm along [020], indicating stress-free rafting. Elemental mapping revealed substantial redistribution of key alloying elements: Al content in γ′ precipitates increased by 2.6 at.%, while Cr in the γ channels rose by 5.9 at.%. These quantitative results demonstrate that SANS provides reliable, bulk-statistical insights into nanoscale channel geometry, highlighting its critical role in influencing elemental diffusion kinetics and microstructural evolution during thermal exposure. Full article

The performance of resin anchoring agents in deep coal mine roadways is significantly compromised by water-bearing and chemically aggressive conditions, posing a major threat to support system reliability. This study aims to systematically quantify this performance deterioration and develop a more resilient material solution for these challenging environments. A comprehensive experimental program was conducted, including uniaxial compression, pull-out, and interface shear tests, accompanied by the systematic improvement of the resin formulation and microstructural analysis via Scanning Electron Microscopy (SEM). The results showed that increasing borehole water content to 30% reduced the compressive strength of conventional resin by over 40%, while acidic environments (pH = 5) caused a 70% drop in its interfacial shear strength. In contrast, an improved formulation incorporating hydroxypropyl acrylate and a super absorbent polymer (SAP) exhibited a 20% higher initial strength, maintained over 85% of its strength under water saturation, and retained functional residual strength in acidic conditions. SEM analysis confirmed that the improved resin’s denser microstructure suppressed interfacial microcrack formation. The findings demonstrate that the improved formulation provides a robust material basis for enhancing the long-term durability and safety of anchorage support systems in extreme underground engineering environments. Full article

Photocatalytic oxidation technology harnesses solar energy for pollutant mineralization, presenting significant potential for environmental applications. A critical bottleneck remains the development of high-performance photocatalysts. This study centers on the non-metallic semiconductor material graphitic carbon nitride (g-C₃N₄). To overcome the inherent limitations of pristine g-C₃N₄, including limited surface area, rapid charge carrier recombination, and inadequate active sites, it implements surface engineering strategies employing acidic (H₂SO₄) or basic (K₂CO₃) agents to modulate microstructure, introduce defect sites (cyano/amino groups), and optimize bandgap engineering. These modifications synergistically enhanced photogenerated charge carrier separation efficiency and surface reactivity, leading to efficient dye degradation. Notably, the K₂CO₃-modified catalyst (g-C₃N₄-OH), synthesized with a mass ratio of m(g-C₃N₄):m(K₂CO₃) = 1:1, achieved 92.2% Rhodamine B degradation within 50 min under visible light, surpassing pristine g-C₃N₄ (20.6%), the optimized H₂SO₄-modified sample (g-C₃N₄-HS, 60.9%), and even template-synthesized g-C₃N₄-SBA (79.6%). The g-C₃N₄-OH catalyst demonstrated exceptional performance under both visible light and natural solar illumination. Combining facile synthesis, cost-effectiveness, superior activity, and robust stability, this work provides a novel approach for developing high-efficiency non-metallic photocatalysts applicable to dye wastewater. Full article

Graphite nodularity is a key indicator for evaluating the microstructure quality of ductile iron and plays a crucial role in ensuring product quality and enhancing manufacturing efficiency. Existing research often only focuses on a single type of feature and fails to utilize multi-source information in a coordinated manner. Single-feature methods are difficult to comprehensively capture microstructures, which limits the accuracy and robustness of the model. This study proposes a hybrid estimation model for the graphite nodularity of ductile cast iron based on multi-source feature extraction. A comprehensive feature engineering pipeline was established, incorporating geometric, color, and texture features extracted via Hue-Saturation-Value color space (HSV) histograms, gray level co-occurrence matrix (GLCM), Local Binary Pattern (LBP), and multi-scale Gabor filters. Dimensionality reduction was performed using Principal Component Analysis (PCA) to mitigate redundancy. An improved watershed algorithm combined with intelligent filtering was used for accurate particle segmentation. Several machine learning algorithms, including Support Vector Regression (SVR), Multi-Layer Perceptron (MLP), Random Forest (RF), Gradient Boosting Regressor (GBR), eXtreme Gradient Boosting (XGBoost) and Categorical Boosting (CatBoost), are applied to estimate graphite nodularity based on geometric features (GFs) and feature extraction. Experimental results demonstrate that the CatBoost model trained on fused features achieves high estimation accuracy and stability for geometric parameters, with R-squared (R²) exceeding 0.98. Furthermore, introducing geometric features into the fusion set enhances model generalization and suppresses overfitting. This framework offers an efficient and robust approach for intelligent analysis of metallographic images and provides valuable support for automated quality assessment in casting production. Full article

With the acceleration of global aging and the rising incidence of stroke, the demand for lower limb rehabilitation has been steadily increasing. Traditional therapeutic methods can no longer meet the growing needs, which has led to the widespread application of robotic solutions to address labor shortages. In this context, this paper presents a hierarchical and distributed control system based on ROS 2 and Micro-ROS. The distributed architecture decouples functional modules, improving system maintainability and supporting modular upgrades. The control system consists of a three-layer structure, including a high-level controller, Jetson Nano, for gait data processing and advanced command generation; a middle-layer controller, ESP32-S3, for sensor data fusion and inter-layer communication bridging; and a low-level controller, STM32F405, for field-oriented control to drive the motors along a predefined trajectory. Experimental validation in both early and late rehabilitation stages demonstrates the system’s ability to achieve accurate trajectory tracking. In the early rehabilitation stage, the maximum root mean square error of the joint motors is 1.143°; in the later rehabilitation stage, the maximum root mean square error of the joint motors is 1.833°, confirming the robustness of the control system. Additionally, the hierarchical and distributed architecture ensures maintainability and facilitates future upgrades. This paper provides a feasible control scheme for the next generation of lower limb rehabilitation robots. Full article

The convergence of Industrial Internet of Things (IIoT) and digital twin technology offers new paradigms for process automation and control. This paper presents an integrated IIoT and digital twin framework for intelligent control of a gas–liquid separation unit with interacting flow, pressure, and differential pressure loops. A comprehensive dynamic model of the three-loop separator process is developed, linearized, and validated. Classical stability analyses using the Routh–Hurwitz criterion and Nyquist plots are employed to ensure stability of the control system. Decentralized multi-loop proportional–integral–derivative (PID) controllers are designed and optimized using the Integral Absolute Error (IAE) performance index. A digital twin of the separator is implemented to run in parallel with the physical process, synchronized via a Kalman filter to real-time sensor data for state estimation and anomaly detection. The digital twin also incorporates structured singular value ($\mu$) analysis to assess robust stability under model uncertainties. The system architecture is realized with low-cost hardware (Arduino Mega 2560, MicroMotion Coriolis flowmeter, pneumatic control valves, DAC104S085 digital-to-analog converter, and ENC28J60 Ethernet module) and software tools (Proteus VSM 8.4 for simulation, VB.Net 2022 version based human–machine interface, and ML.Net 2022 version for predictive analytics). Experimental results demonstrate improved control performance with reduced overshoot and faster settling times, confirming the effectiveness of the IIoT–digital twin integration in handling loop interactions and disturbances. The discussion includes a comparative analysis with conventional control and outlines how advanced strategies such as model predictive control (MPC) can further augment the proposed approach. This work provides a practical pathway for applying IIoT and digital twins to industrial process control, with implications for enhanced autonomy, reliability, and efficiency in oil and gas operations. Full article

Micro-combustion-powered thermoelectric generators (μ-CPTEGs) combine the high energy density of hydrocarbons with solid-state conversion, offering compact and refuelable power for long-endurance electronics. Such characteristics make μ-CPTEGs particularly promising for aerospace systems, where conventional batteries face serious limitations. Their achievable performance hinges on how a swirl-stabilized flame transfers heat into the hot ends of thermoelectric modules. This study uses a conjugate CFD framework coupled with a lumped parameter model to examine how input power and equivalence ratio shape the flame/flow structure, temperature fields, and hot-end heating in a swirl combustor-powered TEG. Three-dimensional numerical simulations were performed for the swirl combustor-powered TEG, varying the input power from 1269 to 1854 W and the equivalence ratio from φ = 0.6 to 1.1. Results indicate that the combustor exit forms a robust “annular jet with central recirculation” structure that organizes a V-shaped region of high modeled heat release responsible for flame stabilization and preheating. At φ = 1.0, increasing Q_in from 1269 to 1854 W strengthens the V-shaped hot band and warms the wall-attached recirculation. Heating penetrates deeper into the finned cavity, and the central-plane peak temperature rises from 2281 to 2339 K (≈2.5%). Consistent with these field changes, the lower TEM pair near the outlet heats more strongly than the upper module (517 K to 629 K vs. 451 K to 543 K); the inter-row gap widens from 66 K to 86 K, and the incremental temperature gains taper at the highest power, while the axial organization of the field remains essentially unchanged. At fixed Q_in = 1854 W, raising φ from 0.6 to 1.0 compacts and retracts the reaction band toward the exit and weakens axial penetration; the main-zone temperature increases up to φ = 0.9 and then declines for richer mixtures (peak 2482 K at φ = 0.9 to 2289 K at φ = 1.1), cooling the fin section due to reduced transport, thereby identifying φ = 0.9 as the operating point that best balances axial penetration against dilution/convective-cooling losses and maximizes the TEM hot-end temperature at the fixed power. Full article

This study adopts a systems perspective to examine the persistent effects of China’s One-Child Policy (OCP) on the subjective well-being of older adults, emphasizing structural persistence, reinforcing feedback, and path-dependent lock-in in complex socio-technical systems. Using nationally representative data from the China Longitudinal Aging Social Survey (CLASS-2014), we exploit the OCP’s formal rollout at the end of 1979—operationalized with a 1980 cutoff—as a quasi-natural experiment. A Fuzzy Regression Discontinuity (FRD) design identifies the Local Average Treatment Effect of being an only-child parent on late-life well-being, mitigating endogeneity from selection and omitted variables. Theoretically, we integrate three lenses—policy durability and lock-in, intergenerational support, and life course dynamics—to construct a cross-level transmission framework: macro-institutional environments shape substitution capacity and constraint sets; meso-level family restructuring reconfigures support network topology and intergenerational resource flows; micro-level life-course processes accumulate policy-induced adaptations through education, savings, occupation, and residence choices, with effects materializing in old age. Empirically, we find that the OCP significantly reduces subjective well-being among the first generation of affected parents decades later (2SLS estimate ≈ −0.23 on a 1–5 scale). The effects are heterogeneous: rural residents experience large negative impacts, urban effects are muted; men are more adversely affected than women; and individuals without spouses exhibit greater declines than those with spouses. Design validity is supported by a discontinuous shift in fertility at the threshold, smooth density and covariate balance around the cutoff, bandwidth insensitivity, “donut” RD robustness, and a placebo test among ethnic minorities exempt from strict enforcement. These results demonstrate how demographic policies generate lasting impacts on elderly well-being through transforming intergenerational support systems. Policy implications include strengthening rural pension and healthcare systems, expanding community-based eldercare services for spouseless elderly, and developing complementary support programs. Full article

Short fibre-reinforced polymers (SFRPs) are increasingly used in structural applications where mechanical integrity under complex loading is critical. However, conventional modelling approaches often fail to accurately predict mechanical behaviour in weldline regions formed during injection moulding, where microstructural anomalies and pre-existing damage significantly degrade performance. This study addresses these limitations by extending a hybrid micro–macromechanical constitutive framework to incorporate localised initial damage at weldlines. Calibration and validation of the model were conducted using directional tensile tests on dumbbell-shaped polyamide 66 specimens reinforced with 25 wt% glass fibres, featuring controlled weldline geometry. Digital image correlation (DIC) was employed to capture strain fields, while injection moulding simulations provided fibre orientation distributions and weldline positioning. Results demonstrate that incorporating initial damage and its independent evolution for the cold weld region significantly improves prediction accuracy in weldline zones without compromising model efficiency. The proposed approach can be integrated seamlessly with existing finite element framework and offers a robust solution for simulating SFRP components with weldlines, enhancing reliability in safety-critical applications. Full article

Potassium–selenium (K-Se) batteries have emerged as a promising energy storage system in view of their high theoretical energy density and low cost. However, their practical application is restricted due to challenges such as polyselenide shuttling, low redox activity, and significant cathode volume expansion during cycling, leading to inferior Coulombic efficiency and a short cycling lifespan. Carbon-based materials, with their superior electronic conductivity, adjustable pore structures, and robust chemical stability, have been extensively studied and employed as cathode materials in K-Se batteries, demonstrating remarkable potential in addressing the above-mentioned issues. Considering the rapidly growing research interest in this topic in recent years, herein, we comprehensively summarize recent advances in the application of carbon-based materials as cathodes in K-Se batteries. First, we introduce the properties, key challenges, and optimization strategies of K-Se batteries, including encapsulating Se within carbon materials, engineering chemisorptive hosts, and electrocatalyzing redox reactions. Furthermore, we discuss the relationship between fabrication strategies, micro/nanostructures, and electrochemical performances. Finally, we propose future prospects for the rational design and application of carbon-based cathodes in K-Se batteries and other alkaline metal–chalcogen batteries. Full article

Multifunctional coatings integrating high transparency, thermal insulation, and self-cleaning properties are critically needed for optical devices and energy-saving applications, yet simultaneously optimizing these functions remains challenging due to material and structural limitations. This study designed a superhydrophobic transparent thermal insulation coating via synergistic co-construction of micro–nano structures using antimony-doped tin oxide (ATO) and SiO₂ nanoparticles dispersed in an epoxy resin matrix, with surface modification by perfluorodecyltriethoxysilane (PFDTES) and γ-glycidyl ether oxypropyltrimethoxysilane (KH560). The optimal superhydrophobic transparent thermal insulating (SHTTI) coating, prepared with 0.6 g SiO₂ and 0.8 g ATO (SHTTI-0.6-0.8), achieved a water contact angle (WCA) of 162.4°, sliding angle (SA) of 3°, and visible light transmittance of 72% at 520 nm. Under simulated solar irradiation, it reduced interior temperature by 7.3 °C compared to blank glass. The SHTTI-0.6-0.8 coating demonstrated robust mechanical durability by maintaining superhydrophobicity through 40 abrasion cycles, 30 tape-peel tests, and sand impacts, combined with chemical stability, effective self-cleaning capability, and exceptional anti-icing performance that prolonged freezing time to 562 s versus 87 s for blank glass. This work provides a viable strategy for high-performance multifunctional coatings through rational component ratio optimization. Full article

Generating non-standard fonts, such as running script (e.g., XingShu), poses significant challenges due to their high stroke continuity, structural flexibility, and stylistic diversity, which traditional component-based prior knowledge methods struggle to model effectively. While diffusion models excel at capturing continuous feature spaces and stroke variations through iterative denoising, they face critical limitations: (1) style leakage, where large stylistic differences lead to inconsistent outputs due to noise interference; (2) structural distortion, caused by the absence of explicit structural guidance, resulting in broken strokes or deformed glyphs; and (3) style confusion, where similar font styles are inadequately distinguished, producing ambiguous results. To address these issues, we propose a novel skeleton-guided diffusion model with three key innovations: (1) a skeleton-constrained style rendering module that enforces semantic alignment and balanced energy constraints to amplify critical skeletal features, mitigating style leakage and ensuring stylistic consistency; (2) a cross-scale skeleton preservation module that integrates multi-scale glyph skeleton information through cross-dimensional interactions, effectively modeling macro-level layouts and micro-level stroke details to prevent structural distortions; (3) a contrastive style refinement module that leverages skeleton decomposition and recombination strategies, coupled with contrastive learning on positive and negative samples, to establish robust style representations and disambiguate similar styles. Extensive experiments on diverse font datasets demonstrate that our approach significantly improves the generation quality, achieving superior style fidelity, structural integrity, and style differentiation compared to state-of-the-art diffusion-based font generation methods. Full article

Diamond-like carbon (DLC) films are valued for their high hardness and wear resistance, but their application in harsh environments is limited by high internal stress and poor corrosion resistance. Co-doping with transition metals offers a promising route to overcome these drawbacks by tailoring microstructure and enhancing multifunctional performance. However, the synergistic effects of Ni and Cr co-doping in DLC remain underexplored. In this study, Ni and Cr co-doped DLC (NiCr-DLC) films were fabricated using filtered cathodic vacuum arc deposition (FCVAD). By varying the C₂H₂ flow rate, the carbon content and microstructure evolved from columnar to fine-grained and compact structures. The optimized film (F55) achieved an ultralow surface roughness (Sa = 0.26 nm), even smoother than the Si substrate. The Ni–Cr co-doping promoted a nanocomposite structure, yielding a maximum hardness of 15.56 GPa and excellent wear resistance (wear rate: 4.45 × 10⁻⁷ mm³/N·m). Electrochemical tests revealed significantly improved corrosion resistance compared to AISI 304L stainless steel, with F55 exhibiting the highest corrosion potential, the lowest current density, and the largest impedance modulus. This work demonstrates that Ni-Cr co-doping effectively enhances the mechanical and corrosion properties of DLC films while improving surface quality, providing a viable strategy for developing robust, multifunctional protective coatings for demanding applications in aerospace, automotive, and biomedical systems. Full article

This research evaluates the stabilization of a clay collected from the northern expansion zone of Cartagena de Indias, Colombia. Laboratory analyses, including particle size distribution, Atterberg limits, compaction, specific gravity, and XRF/XRD, classified the soil as a highly plastic clay (CH) with moderate dispersivity, as confirmed by pinhole and crumb tests. The soil was treated with 3–9% lime, with and without the addition of NaCl (0% and 2%), and tested for unconfined compressive strength (q_u), small-strain stiffness (G_o), and microstructural properties under curing periods of 14 and 28 days at two compaction densities. Results showed that lime significantly improved mechanical behavior, while the inclusion of NaCl further enhanced q_u (up to 185%) and G_o (up to 3-fold), particularly at higher lime contents and curing times. Regression models demonstrated that both q_u and G_o follow power-type relationships with the porosity-to-lime index, with consistent exponents (−4.75 and −5.23, respectively) and high coefficients of determination (R² > 0.79). Normalization of the data yielded master curves with R² values above 0.90, confirming the robustness of the porosity-to-lime framework as a predictive tool. The G_o/q_u ratio obtained (3737.4) falls within the range reported for cemented geomaterials, reinforcing its relevance for comparative analysis. SEM observations revealed the transition from a porous, weakly aggregated structure to a dense matrix filled with C–S–H and C–A–H gels, corroborating the macro–micro correlation. Overall, the combined use of lime and NaCl effectively converts dispersive clays into non-dispersive, mechanically improved geomaterials, providing a practical and sustainable approach for stabilizing problematic coastal soils in tropical environments. Full article

Considerable research in recent years has examined the reuse of tailings; however, the lack of particle cohesion limits their application as construction materials. Therefore, this study assessed the stabilization of ultrafine iron ore tailings using an acrylic–styrene copolymer. Geotechnical characterization and polymer dosage, hydromechanical and microstructural tests were carried out, including unconfined compressive strength (UCS), permeability, scanning electron microscopy (SEM) and microtomography (μCT). The polymer effectively enhanced the mechanical behavior of the tailings, increasing the UCS from 49 kPa for untreated material to 2114 kPa and 3324 kPa for 30% and 40% polymer content, respectively. A robust power-law model (R² ≥ 0.90), based on the porosity/volumetric polymer index (η/Pᵢᵥ), was developed to predict strength, showing that mechanical gains can be achieved by increasing either polymer content or dry density, as supported by statistical analyses. Permeability remained on the order of 10⁻⁶ cm/s regardless of polymer addition, indicating that the polymer does not fill voids but instead acts as a binding agent, as confirmed by SEM and μCT analyses. Overall, this study establishes a technically feasible and sustainable approach for tailings management, highlighting the potential of polymer stabilization to turn environmentally challenging tailings into functional geotechnical materials. Full article