Search Results (523)

Perovskite manganites (AMnO₃) and perovskite-like manganites (A’_1−xA_xMnO₃) are complex oxide materials that have attracted significant attention from the scientific community in recent years due to their structural flexibility, mixed-valence state, tunable electronic configuration, and multifunctional properties. This review systematically analyzes the synthesis methods, structural classification, and physicochemical characterization of perovskite manganites, as well as their magnetic, optical, electrical, dielectric, and catalytic properties. The influence of solid-state reactions, sol–gel, Pechini, hydrothermal, co-precipitation, microwave, and other mild chemical approaches on phase purity, morphology, particle size, and oxygen stoichiometry was examined. The structural diversity of perovskite and perovskite-like manganites, including simple ABO₃, double perovskites, multilayer, and low-dimensional systems, was characterized in relation to their functional properties. The review discussed the capabilities of methods for synthesizing and analyzing morphological properties, demonstrating the role of doping, cation substitution, oxygen vacancies, and Jahn–Teller distortions in controlling material properties. Prospects for the application of perovskite manganites in spintronics, magnetocaloric cooling, photocatalysis, gas-sensing devices, and energy conversion and storage systems were analyzed. This review highlights the structure–property–application relationship in perovskite manganites. Full article

Lightweight polymer composites with effective electromagnetic interference (EMI) shielding are of increasing interest for advanced electronic and aerospace applications; however, conventional glass fiber-reinforced polymers (GFRPs) exhibit inherently low electrical conductivity, limiting their shielding performance. In this study, a hierarchical hybrid conductive architecture was developed by integrating graphene-coated multiaxial glass fiber fabrics with carbon black (CB)-reinforced epoxy matrices to enhance EMI shielding behavior in the X-band (8–12 GHz). Graphene coatings were deposited onto glass fibers via a surfactant-assisted ultrasonic dispersion method, while carbon black (0–1 wt.%) was incorporated into the epoxy matrix using ultrasonication-assisted mixing. Multilayer composites were fabricated using a vacuum bagging process. X-ray diffraction analysis revealed that the composites retained a predominantly amorphous epoxy/glass fiber matrix while exhibiting broad carbon-related diffraction features associated with disordered graphitic domains. Electrical conductivity measurements indicated that all composites remained in the insulating regime (~10⁻⁹ S/m), suggesting that a fully interconnected conductive network was not established within the investigated filler range. Despite the absence of a continuous conductive network, measurable EMI shielding performance was achieved. The composite containing 0.25 wt.% CB exhibited the highest shielding effectiveness, reaching approximately 12 dB at ~11.2 GHz. Analysis of the shielding contributions showed that absorption contributions (SEA) were consistently higher than reflection contributions (SER) across the studied frequency range. Morphological observations revealed that well-dispersed CB at low loading facilitated the formation of localized conductive domains that may contribute to tunneling-assisted polarization and interfacial charge accumulation. At higher CB contents, particle agglomeration reduced dispersion quality and limited effective pathway formation, while dynamic mechanical analysis indicated enhanced stiffness at low CB loading. FTIR results confirmed the absence of new chemical bonding, indicating that CB acts as a physically dispersed conductive filler. Overall, the results show that effective EMI shielding can be achieved in electrically insulating composites through the combined effect of hierarchical structural design and localized conductive features. This approach provides a practical pathway for developing lightweight EMI shielding materials with controlled filler loading and preserved structural integrity for aerospace and electronic applications. Full article

PM_2.5 is a major air pollutant that threatens urban air quality and public health. Its concentration is influenced by both meteorological conditions and air pollutants, exhibiting complex nonlinear and temporal characteristics. Traditional statistical methods are limited in their ability to model complex relationships among environmental variables, while machine learning models still require improvements in hyperparameter optimization and interpretability. Therefore, developing an accurate and interpretable PM_2.5 estimation model remains an important research objective. This study used daily air-quality and meteorological data collected in Wuhan from 2016 to 2025 to develop six machine learning models: Decision Tree (DT), Random Forest (RF), XGBoost, LightGBM, Support Vector Machine (SVM), and Multilayer Perceptron (MLP). The Particle Swarm Optimization (PSO) algorithm was employed to optimize the hyperparameters of these models. By comparing the root mean square error (RMSE), coefficient of determination (R²), and mean absolute error (MAE) of each model on both the training and test sets, the PSO-MLP model was identified as the best-performing model. Furthermore, the Shapley Additive Explanations (SHAP) method was applied to perform both global and local interpretation analyses of the best-performing model. The results indicate that the PSO-MLP model achieved the highest estimation performance among all evaluated models, with an R² value of 0.746 on the test set. SHAP analysis revealed that CO, Temperature (Temp), and NO₂ were the most influential predictors, while all variables exhibited distinct nonlinear relationships with PM_2.5 concentration. These findings may contribute to PM_2.5 concentration estimation, air-quality management, and environmental decision-making. Full article

In this study, manual welding electrodes with varying niobium (Nb) contents (0, 0.05, and 0.1 wt%) were developed for 960 MPa grade low-alloy high-strength steel, and deposited metals were produced through multilayer multipass welding. Microstructural characterization and mechanical testing were performed using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), electron backscatter diffraction (EBSD), and a universal testing machine to investigate the influence of Nb content and elucidate the strengthening mechanisms. The results demonstrate that under identical welding conditions, multipass thermal cycles induced a primary microstructural transformation from martensite to tempered martensite in all deposited metals, which predominantly comprised tempered martensite with minor fractions of bainite and second-phase particles. Increasing Nb content led to significant grain refinement. The second-phase particles exhibited sizes of 0.158 μm, 0.176 μm, and 0.168 μm, respectively, with volume fractions of 5.69%, 5.82%, and 5.90%. Nb addition substantially enhanced hardness and strength while causing a noticeable reduction in low-temperature impact toughness, though the values remained within acceptable limits. The deposited metal containing 0.05 wt% Nb exhibited optimal comprehensive mechanical properties, with a hardness of 386.7 HV, tensile strength of 1060 MPa, yield strength of 962 MPa, and Charpy impact energies of 41.95 J and 33.17 J at −40 °C and −60 °C, respectively. Theoretical calculations revealed that the dislocation strengthening contribution in martensite increased from 526 MPa to 600 MPa with increasing Nb content, representing the dominant strengthening mechanism, while grain refinement strengthening increased from 135.5 MPa to 157.6 MPa. Full article

As multilayer ceramic capacitors continue to evolve toward thinner dielectric layers and lower cost, the development of barium titanate powders combining nano-scale particle size with reduction resistance has become a critical industry demand. In this paper, BT-xOH nano-powders with different hydroxyl defect contents were prepared by the sol–gel–hydrothermal method through adjusting the concentration of the mineralizer KOH, and the regulation mechanism of hydroxyl defects on the reduction resistance of barium titanate ceramics was systematically investigated. The research shows that for BT-xOH ceramics sintered under a reducing atmosphere, hydroxyl defects are converted into oxygen vacancies, disrupting the long-range order of ferroelectric domains and associating with barium vacancies to form [${\mathrm{V}}_{\mathrm{Ba}}^{‘’}\text{-}{\mathrm{V}}_{\mathrm{O}}^{..}$] defect dipoles. These dipoles, in coordination with the increase in grain boundary density, enhance the charge carrier migration barrier and the suppression of oxygen vacancies and electronic conductivity by the grain boundary space charge layer, resulting in a resistivity on the order of 10¹¹ Ω·cm under a reducing atmosphere. Meanwhile, oxygen vacancies generate a pinning effect at grain boundaries, achieving the effect of inhibiting grain growth. This study reveals the microscopic mechanism by which the reduction resistance is enhanced through the regulation of intrinsic hydroxyl defects in the powder, providing a new technical pathway for dielectric materials used in high-performance base metal electrode MLCCs. Full article

Gadolinium is a rare-earth element that is promising for the field of biomedicine due to its unique properties that enhance image quality, giving it high potential in targeted cancer therapy, antimicrobial treatments, etc. The disadvantage of Gd-containing materials is their high toxicity. In this work, ensembles of Fe and Al₂O₃ nanoparticles were fabricated by the electric explosion of wire and Gd ribbons using rapid quenching techniques. Stable Fe, Fe/Gd and Fe/Gd/Al₂O₃ aqueous suspensions with a Z-potential of about −54 mV were fabricated by the ball-milling mechanosynthesis of Fe (100%), Fe and Gd (70 and 30 wt. % accordingly) and Fe, Al₂O_3, and Gd (69, 30 and 1 wt.% accordingly). Fillers from suspensions were used for the synthesis of epoxy composites mimicking natural tissue with embedded magnetic particles. The concentration range for synthesized epoxy composites (0, 5, 10, and 15 wt.% of the filler) corresponded to the biomedical range of interest. Thin-film magnetoimpedance (MI) elements were prepared by a sputtering technique: conventional [FeNi/Cu]₅/Cu/[Cu/FeNi]₅ (NP) element and [FeNi/Cu]₅/Cu/[Cu/P{FeNi]₅} element with patterned top multilayer (SqP). They showed a maximum MI ratio of about 160% for NP and about 60% for SqP. MI sensor response was affected by the presence of filled magnetic composites in the shape of cylinders (5 mm × 4 mm) situated at about 1 mm due to the stray fields in the filler. MI response showed a linear dependence on the filler concentration for each selected position. These results open the possibility to develop new iron- and gadolinium-containing materials for simultaneous magnetic imaging and detection by magnetic field sensors, extending the functional properties of Fe/Gd materials for biomedical devices and therapies. Full article

As power grids transition towards highly renewable generation on a global scale, maintaining dynamic stability is becoming a major challenge. Replacing traditional synchronous generators with inverter-based renewables strips the grid of rotational inertia, leaving active distribution networks highly vulnerable to frequency deviations and voltage spikes. To avoid expensive poles and wires upgrades, Battery Energy Storage Systems (BESS) are increasingly being deployed as Non-Network Solutions (NNS). However, the current literature reveals a distinct gap between the macro-scale economic planning of these storage assets and the micro-scale dynamic control actually required to keep the grid resilient. To address this gap, this review proposes a multi-layer deterministic synthesis framework that links physical renewable modelling, degradation-aware techno-economic planning, deterministic forecasting, and EMS dispatch through offline time-domain control validation for AC-microgrid energy storage integration. The research examines how advanced central control units within battery management systems can rigorously and jointly estimate State of Charge (SoC) and State of Energy (SoE) to ensure accurate grid-aware dispatch. Furthermore, the study explores the integration of degradation-aware economic modelling in HOMER Pro with dynamic transient control in MATLAB/Simulink R2025b, driven by hybrid metaheuristic optimization algorithms like Grey Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO). This analysis demonstrates that integrating energy storage must be treated as a tightly coupled multidimensional optimization problem to successfully deliver the secure and sustainable infrastructure needed to solve the modern energy trilemma. Full article

Micro and nanoplastics (MNPs) are increasingly recognized as contaminants in food systems; however, the specific packaging elements responsible for particle release remain poorly resolved. Most studies treat packaging as a single material category, without covering distinct contributions from the different units of modern food contact materials (FCMs). We propose a packaging structure taxonomy based on functional elements: container (C), closure (CL), and functional layers (F), including operational interfaces (+I), designed to enable components attribution of possible origins of plastic fragments in foods and beverages. Through a structured synthesis of the current literature, we map the primary processes leading to MNP generation across these modules, including tribological abrasion at closure contact interfaces, thermally driven polymer degradation in containers and delamination or shedding from coatings, adhesives and multilayer structures. Available evidence indicates that repeated mechanical actions such as opening and closing cycles can generate measurable particle release from closure assemblies. The proposed C/CL/F + I framework introduces standardized descriptors and reporting units that improve comparability across studies and supports origin attribution. By explicitly separating packaging parts and their operational interaction zones, the taxonomy provides a methodological bridge between analytical microplastic detection and engineering strategies aimed at minimizing particle formation. Its adoption can facilitate harmonized experimental design, strengthen regulatory risk assessment and guide the development of packaging configurations that minimize plastic particle shedding into foods. Full article

Glitter is a distinctive and largely overlooked form of primary microplastic. Unlike more commonly studied microplastics, glitter particles are typically flat, highly reflective, multi-layered, and are composed of polymers such as polyethylene terephthalate, polyvinyl chloride with metallic coatings and a wide range of additives. In response to regulatory restrictions on intentionally added microplastics and increasing consumer demand, “eco-friendly” alternatives based on modified regenerated cellulose, cellulose nanocrystals, or mica have been introduced, although their environmental safety remains insufficiently characterized. This review synthesizes current knowledge on the environmental occurrence and ecotoxicological effects of both conventional and biodegradable glitters. A systematic literature search in Scopus identified 15 peer-reviewed experimental studies meeting predefined inclusion criteria. Evidence spans a wide range of taxa, including bacteria (i.e., Aliivibrio fischeri), microalgae and cyanobacteria (i.e., Phaeodactylum tricornutum, Raphidocelis subcapitata, Microcystis aeruginosa), aquatic plants (i.e., Lemna minor, Egeria densa), marine and freshwater invertebrates as crustaceans (i.e., Daphnia magna), bivalves (i.e., Mytilus galloprovincialis), sea urchins (i.e., Paracentrotus lividus), brine shrimp (Artemia sp.) and terrestrial soil fauna (Eisenia fetida, Folsomia candida). Results indicate that glitter cannot be treated as a uniform stressor: biological responses vary markedly with particle size, shape, colour, polymer type, additive composition, and weathering time, and leachates often exert stronger effects than intact particles. Reported impacts include impaired photosynthesis and growth, oxidative stress, developmental abnormalities, altered energy metabolism, and reduced reproduction. Substantial gaps remain regarding environmental concentrations, ageing processes, mixture effects, and long-term ecological consequences, particularly for biodegradable glitters. Addressing these gaps will require realistic exposure scenarios, mesocosm and field studies, and integrated chemical–biological approaches to support robust risk assessment and safer material design. Full article

A capacitor electrode has been developed, obtained by electrophoretically filling the nanosized pores of anodic alumina with carbon particles and PVDF. By pre-thinning the barrier anode layer, direct contact of carbon with the aluminum current collector has been achieved. The multilayer electrode from {carbon particles and PVDF}/{carbon black and porous AAO}/{aluminum current collector} was studied using Raman spectroscopy, scanning electron microscopy, energy-dispersive X-ray analysis, and atomic force microscopy. The analyses demonstrate the highly developed surface of the electrodes and the good binding ability of the PVDF. The electrochemical properties of the electrodes were investigated in a 0.5 M Na₂SO₄ aqueous electrolyte using cyclic voltammetry, electrochemical impedance spectroscopy, and galvanostatic charge–discharge. The electrode allows operation at a high voltage window of 5.75 V. The electrochemical results show that the electrodes have a specific capacitance of 4.25 ± 0.35 F g⁻¹, a specific energy density of 19.3 Wh kg⁻¹ and specific power of about 5600 W kg⁻¹ with stable operation over 10,000 cycles. Therefore, the strategy of using electrophoretic deposition of carbon materials seems promising for obtaining inexpensive capacitive layers with good adhesion to aluminum, operating stably in a wide voltage window. Full article

For the sake of investigating the theoretical design optimization of high-rise plane frames, an optimization model was established by taking the minimum top-story lateral displacement as the objective function and treating material strength, story height, and span length as design variables. The design parameters of the frame were optimized using an Assimilation–Competition Quantum-behaved Particle Swarm Optimization (ACQPSO) algorithm. First, the accuracy and computational efficiency of the ACQPSO algorithm were evaluated using four benchmark functions. Then, a five-span, seven-story reinforced-concrete plane frame with a total span of 24 m and a total height of 34 m was taken as a case study. The cross-sectional dimensions of the beams and columns were determined according to relevant design specifications, and the top-story lateral displacement calculated by the D-value method was verified using the Finite Element Method (FEM), confirming its accuracy and effectiveness. Finally, a parametric analysis was carried out to investigate the effects of material strength, story height, span length, and member cross-sectional dimensions on the objective function. The results indicate that story height and column concrete strength have a greater influence on the top-story lateral displacement, whereas the effect of span length is relatively small. In addition, the cross-sectional dimensions of beams and columns affect the top-story lateral displacement more significantly than beam strength. Full article

Extrusion-based three-dimensional food printing requires inks that can be smoothly extruded while maintaining sufficient structural stability after deposition. In this study, gelatin and κ-carrageenan were first mixed and then subjected to post-mixing pH regulation before spray drying, producing composite powders with different structural states. These powders were incorporated into yellow peach pulp gels to prepare fruit-based printing inks, and their printing performance, extrusion behavior, mechanical properties, particle-size distribution, and microstructure were systematically evaluated. The results showed that the structural state formed during gelatin–κ-carrageenan powder preparation was closely associated with the extrusion stability and shape retention of the final inks. Among the tested formulations, the ink prepared with gelatin–κ-carrageenan powder pre-regulated to pH 4.0 exhibited the best overall printability. Although its pore-area fidelity was slightly lower than that of the sample pre-regulated to pH 3.5, it produced more stable multilayer cylinders and better-defined lattice structures. In addition, the pH 4.0 sample showed the lowest and most stable extrusion force and the highest Young’s modulus, indicating a favorable balance between extrusion flowability and post-deposition support. Microstructural observations and particle-size analysis suggested that pH regulation altered the aggregation state and local morphology of the gelatin–κ-carrageenan system. Samples prepared at higher pH values tended to form larger and less uniform aggregates, which was unfavorable for stable extrusion and shape retention. Overall, post-mixing pH regulation of gelatin–κ-carrageenan provides a practical strategy for improving the printing-related properties of fruit-based gel inks. Full article

Buried-pipeline leakage poses significant safety risks, yet traditional CFD (Computational Fluid Dynamics) simulations are too slow for real-time diagnosis. This study integrates machine learning with interval sampling to develop a fast and interpretable prediction method. From 1.4 billion CFD-generated data points, 140 million representative samples were extracted via 1:10 interval sampling. Using 17 physical features as inputs, we trained and compared XGBoost, LightGBM, and a Multi-Layer Perceptron (MLP). The MLP model demonstrated exceptional performance (R² (R-squared) = 0.9988, RMSE (Root Mean Square Error) = 0.0153), significantly outperforming the tree-based models (R² ≈ 0.93). Three independent sampling runs confirmed its robustness (R² coefficient of variation~0%). SHAP (Shapley Additive Explanations) analysis identified spatial coordinates and leak aperture as the most critical factors, while also revealing the nonlinear influence of soil particle size. This approach offers a high-precision, interpretable, and efficient surrogate model for buried-pipeline leakage warning systems. Full article

Aquaculture wastewater containing tetracycline hydrochloride (TCH) poses significant environmental problems and health risks. We investigated the adsorption of TCH onto phosphoric acid-activated corncob biochar (PCC) as a sustainable and efficient removal strategy. PCC was synthesized from cob feedstock activated by phosphoric acid under a pyrolysis temperature of 300 °C in a limited-air atmosphere. It was characterized extensively, revealing a high specific surface area (1071.75 m²/g), high porosity with total pore volume of 0.912 cm³/g, and abundant surface functional groups including phosphate, carboxylic, and amine groups. Batch adsorption experiments demonstrated an ultrahigh adsorption capacity for TCH, with a maximum theoretical capacity (Langmuir model) of 953.62 mg/g at 313 K. Its adsorption isotherms transfer from Langmuir type to Freundlich type as temperature rises, indicating a transition from monolayer to multilayer adsorption. The adsorption kinetics were governed by a synergistic mechanism involving surface adsorption and a pore-filling effect (intra-particle diffusion). Critically, the adsorption dynamics exhibit an intra-particle diffusion-controlled process at a low pH (3.0) during the final stage of adsorption. Strong hydrogen bonding led to high initial adsorption rates, and the adsorption converted to diffusion-controlled mode eventually. In contrast, at higher pH (≥7.0), electrostatic repulsion between PCC adsorbents and TCH molecules hindered intra-particle diffusion, causing the final adsorption stage to deviate from diffusion control. This work provides comprehensive insights into the pH-dependent interfacial interactions and kinetics governing TCH removal by corncob-derived, phosphoric acid-activated biochar. Full article

This research aimed to develop a rapid, non-destructive, and accurate method for detecting adulteration in turmeric using Visible–Near-Infrared (UV/Vis and NIR) spectroscopy combined with machine learning algorithms. Spectral data from the samples were collected and analyzed in two ranges: 170–870 nm (UV/Vis) and 900–2170 nm (NIR). Four supervised learning algorithms, including Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), the Multilayer Perceptron (MLP) neural network, and Decision Tree, were evaluated for modeling. To quantitatively assess model performance, we employed not only the accuracy metric but also complementary performance indicators including precision, recall, and the F1-score to provide a more comprehensive evaluation of classification effectiveness. The models developed in the 900–2170 nm spectral range demonstrated highly significant performance, with most models achieving 100% accuracy on the independent test set. To reduce data dimensionality and enhance computational efficiency, a hybrid feature selection method combining SVM with five algorithms—League Championship Algorithm (LCA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and Imperialist Competitive Algorithm (ICA)—was employed. Upon evaluation of each method, the SVM-LCA was selected as the optimal feature selection technique. This algorithm successfully extracted the most effective wavelengths with the highest correlation and lowest error, which maintained or improved the accuracy of the classification models. This study confirms the high potential of UV/Vis and NIR spectroscopy as rapid, non-destructive, and precise tools for detecting adulteration in turmeric. The findings can pave the way for the development of intelligent quality control systems in the food and pharmaceutical industries, playing a crucial role in ensuring consumer health and safety. Full article