Search Results (2,516)

This study examined Kefiran, an exopolysaccharide derived from milk kefir grains, as a novel biopolymer for encapsulating phenolic extracts from sunflower cake and its antimicrobial properties in the development of natural and functional food ingredients. Kefiran was obtained from kefir grains using three extraction protocols: hot water (M1), hot water with 30% trichloroacetic acid (M2), and mild heat combined with ultrasound at 60 °C (M3). The ultrasound-assisted method produced the highest carbohydrate concentration. Spectrophotometric assays (phenol–sulfuric and Bradford), Fourier transform infrared spectroscopy, scanning electron microscopy, thermogravimetric analysis, and water-holding capacity were employed to characterize the composition, structure, and morphology of the extracts, revealing well-preserved polysaccharide fingerprints and a highly porous microstructure, consistent with their potential application in food systems. Kefiran was then evaluated as an encapsulating agent in complex coacervation at pH 3.75, using three Kefiran-based wall formulations (M1, M2, and M3) with gum arabic and whey protein isolate (WPI) as co-wall materials, and their performance was compared with gum arabic and WPI controls. Across formulations, coacervate microcapsules achieved high encapsulation efficiencies (83–93%), tunable particle sizes, and predominantly negative zeta potentials, indicative of good colloidal stability. The Kefiran extract and coacervate microcapsules demonstrated significant antioxidant and antimicrobial activity against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Candida albicans, with minimum inhibitory concentrations ranging from 250 to 1000 µg/mL. The findings support ultrasound-extracted Kefiran as a multifunctional biopolymer suitable for bioactive delivery and as a natural antimicrobial component in advanced functional food formulations. Full article

To efficiently degrade tetracycline (TC) antibiotic pollution, cobalt-based (Co-OMCs/F) and cobalt–copper bimetallic ((Co+Cu)-OMCs/F) monolithic mesoporous carbon catalysts were synthesized using resorcinol–formaldehyde resin as a carbon precursor, with hexamethylenetetramine (HMT) and formaldehyde (CH₂O) as crosslinking agents, followed by high-temperature carbonization under N₂. The materials were characterized by XRD, SEM-EDX, HRTEM, and EPR. Key factors-metal loading, PMS concentration, initial pH, and flow rate-were investigated for their effects on TC degradation. Degradation mechanisms and stability were assessed via radical quenching and continuous-flow cycling tests. Results show optimal performance at a cobalt loading of 0.6 g. Compared to CH₂O, HMT favors a three-dimensional interconnected mesoporous carbon framework with uniform metal distribution and high crystallinity. Under conditions of 25 mg/L TC, 0.33 mmol/L PMS, pH 7, and 2 mL/min flow rate, the (Co+Cu)-OMCs/F (HMT) catalyst achieved ~93% TC degradation over 9 h of continuous operation, and 95% after three reuse cycles, significantly outperforming the single-metal Cu-OMCs/F catalyst. Radical quenching and EPR identified superoxide radicals (·O₂⁻) as the dominant active species (~78% contribution), with sulfate radicals (SO₄^·−), hydroxyl radicals (·OH), and singlet oxygen (¹O₂) playing synergistic roles. The synergistic Co-Cu bimetallic effect, combined with the confinement effect of the mesoporous carbon support and HMT-induced uniform nucleation, endows the catalyst with high activity and long-term stability. This work provides a theoretical basis for designing efficient, reusable, monolithic mesoporous carbon-based PMS activation catalysts for advanced antibiotic wastewater treatment. Full article

Construction materials like steel and concrete have been used for thousands of years; however, their industrial-scale production began relatively recently in the 19th century. These materials are still being improved as the drive to build taller buildings, longer bridges, larger dams, and similar engineering marvels keeps pushing boundaries and requirements to previously unimaginable values. Yet, testing and characterization of construction materials that make all that progress possible are overshadowed in scientific literature by more trendy materials such as graphene, composites, nanomaterials, smart materials, and biomaterials. The objective of this review was to identify, collect, and systematically analyze recent papers in which the researchers performed experimental testing on construction materials to document how state-of-the-art experimental practice extends beyond what standardized protocols prescribe. This paper covers Uniaxial Tensile Testing (UT), Compact Tension C(T), Uniaxial Compression (UC), and Single Edge Notched Bending SEN(B), as they are the most commonly used and best-suited techniques for construction material analysis. State-of-the-art papers featuring these techniques were systematically gathered using AI-assisted literature discovery tools, and their contributions beyond ISO and ASTM standards were identified and summarized. Using this review, material scientists and engineers can quickly discover the most influential and relevant papers with the actual experimental data and can apply the testing procedures described in these papers in their laboratories so they can compare their results with the previously published measurements and make an engineering decision based on appropriate comparisons. Full article

To address the urgent demand for eco-friendly and low-cost catalysts to replace toxic heavy-metal additives in energetic materials, this work focuses on developing biomass-derived copper-doped porous carbon (CuPC) as a high-efficiency catalyst for the thermal decomposition and combustion of molecular perovskite energetic material (H₂dabco)NH₄(ClO₄)₃(DAP-4). Biomass carbonaceous material has garnered extensive attention in many fields, owing to the low cost, high utilization efficiency, and environment protection. Herein, the CuPC catalysts were rationally designed and fabricated via the high-temperature carbonization treatment of biomass carbonaceous material precursor. The catalytic effects of CuPC on the thermal decomposition and combustion characteristics of DAP-4 were systematically investigated. The results revealed that CuPC possessed inherent catalysis property on the decomposition and combustion reaction of DAP-4. Cu_xO_y nanoparticles were uniformly distributed on the surface of carbonized biomass substrates, endowing the catalysts with superior dispersibility. Thermal analysis results indicated that the addition of 5 wt% CuPC-3 reduced the thermal decomposition peak temperature from 378 °C of raw DAP-4 to 350 °C of DAP-4/CuPC-3. Moreover, the apparent activation energy of DAP-4 was notably decreased with the incorporation of CuPC catalysts. The combustion characterization results demonstrated that DAP-4 exhibited a more intense combustion process with the addition of CuPC, accompanied by elevated maximum combustion temperature and enhanced combustion heat. The catalytic mechanism of CuPC on the thermal decomposition and combustion of DAP-4 was further proposed. This work provides a targeted strategy for designing sustainable biomass-based catalysts to optimize the energy release performance of advanced molecular perovskite energetic materials. Full article

With the rapid construction of new power systems characterized by high renewable energy penetration, high power electronics integration, and high voltage levels, the insulation reliability of critical power equipment—including cable accessories, gas-insulated switchgear (GIS), and power electronic modules—faces unprecedented challenges. Field grading materials (FGM), as core functional media for adaptive electric field homogenization and insulation failure prevention, have emerged as a research hotspot spanning materials science, electrical engineering, and polymer engineering. Starting from the current research status of FGM, this review systematically summarizes filler optimization strategies, covering single fillers, hybrid fillers, trace co-fillers, and structural modification approaches. The applications of FGM in transmission cables, GIS, high-voltage electrical machines, and wide-bandgap power electronic modules are then elaborated in detail. Emphasis is placed on performance enhancement routes of FGM, particularly thermal conductivity improvement via constructing three-dimensional thermally conductive networks and intelligent early warning based on thermochromic materials. Finally, the existing bottlenecks of FGM are analyzed in terms of material stability, multi-physical field coupling adaptation, and engineering industrialization. Future development trends are prospected toward high-performance, multifunctional, intelligent, and engineering-oriented FGM. This review aims to provide theoretical references and technical support for the design and application of advanced FGM in new power systems. Full article

Advances in polysaccharide-based polymer matrices have expanded the possibilities for developing controlled-release systems for bioactive compounds. This study evaluated the effect of incorporating maltodextrin (0, 1, 3, and 5% w/w) into films composed of thermoplastic starch (5%) and chitosan (2%) was evaluated with the aim of improving their structural, thermal, mechanical, and surface properties. The films were obtained by solvent casting and characterized by XRD, TGA-DSC, FTIR, SEM, contact angle, and mechanical analysis. X-ray diffraction revealed greater organization in sample TPS-CH-M3 compared with TPS-CH-M0 (23,316.7) and TPS-CH-M5 (18,941.4), indicating a balanced semicrystalline structure. Thermal analyses showed an increase in the glass transition temperature from 63.0 °C to 72.6 °C and a shift in the main degradation step from 308 °C to 311 °C, indicating greater thermal stability. The contact angle decreased from 89.5° to 74°, confirming increased hydrophilicity. SEM micrographs revealed a homogeneous surface in TPS-CH-M0 and controlled roughness in TPS-CH-M3. Mechanical tests recorded the highest tensile strength (12.5 MPa) and elongation (18%) for TPS-CH-M3. FTIR spectra revealed physical interactions without the formation of new chemical bands, while colorimetry showed an increase in yellow hue, suggesting potential applications related to photosensitive materials. Overall, the incorporation of 3% maltodextrin optimized the functional properties of the matrices for potential controlled-release applications. Full article

Carbon fiber-reinforced polymer (CFRP) composites are in urgent demand in the aerospace, new energy vehicle, and wind power sectors owing to their superior specific strength, specific modulus, and lightweight potential. However, molding defects, such as voids, dry spots, and delamination, arising from their anisotropy and weak interlaminar bonding, severely constrain their service performance. Advanced molding technologies represent the key to overcoming this bottleneck. This paper systematically reviews typical advanced molding technologies in the field of CFRP composites, including resin transfer molding (RTM) and vacuum-assisted resin transfer molding (VARTM) in liquid composite molding, autoclave molding and compression molding (CM) in prepreg molding, and automated fiber placement (AFP) and material extrusion (ME) in automated molding. From an integrated perspective of “technological evolution–process characteristics–defect mechanisms–optimization strategies,” this review summarizes the technical principles, development trajectories, and core advantages of each process, analyzes the formation mechanisms of typical defects, including voids, dry spots, delamination, wrinkles, warpage, and melt instability, and summarizes multidimensional optimization advances in process parameter regulation, numerical simulation, resin modification, equipment upgrading, path planning, and thermal management. Furthermore, the differences and complementarities among these processes in terms of molding precision, efficiency, cost, and applicable scope are compared. Finally, future development directions, including digital twins, green low-carbon manufacturing, ultra-large integrated structures, multi-process integration, standardized defect characterization, and low-cost collaborative design, are discussed. This paper aims to provide systematic theoretical references and technical support for the optimization and upgrading, process integration, and industrial application of advanced CFRP molding technologies. Full article

Wire arc additive manufacturing (WAAM) has emerged as a promising technology for producing large-scale metal components due to its high deposition efficiency, low material cost, and design flexibility. However, the widespread industrial adoption of WAAM is hindered by challenges in geometric accuracy, process stability, and defect control, which are closely related to two critical aspects: trajectory planning and real-time weld seam tracking. This review provides a comprehensive and critical analysis of recent advances in both fields, with an emphasis on their interconnection rather than treating them as separate research streams. Unlike existing reviews that primarily summarize path planning algorithms or image processing techniques in isolation, this paper explicitly examines the integration challenges and synergistic potential between offline trajectory optimization and online vision-based monitoring. Key topics include adaptive path strategies for sharp corners and intersections, interlayer filling methods to mitigate heat accumulation and residual stress, as well as passive and active visual sensing technologies for molten pool characterization and defect detection. The review further identifies a persistent gap in closed-loop systems that combine real-time image feedback with dynamic path replanning. Based on the analysis of representative studies, current limitations are discussed and future research directions are proposed, including the development of digital twins, multi-modal data fusion, and reinforcement learning-based adaptive control. This review offers a distinct perspective aimed at advancing intelligent, high-precision WAAM systems for complex metal components. Full article

Glauconite-rich sands can generate authigenic clays during burial, as glauconite breaks down and supplies material for smectite that may subsequently transform into illite. The smectite-to-illite transformation is a key burial diagenetic reaction that strongly influences sandstone reservoir quality; however, the reaction pathways and resulting textures in glauconite-rich sands remain insufficiently documented. To better constrain illitization in glauconitic systems, we conducted four hydrothermal batch experiments using glauconitic greensand from the Arnager Greensand Formation (Bornholm Island, Denmark), reacted with Red Sea water at 80 °C, 150 °C, 200 °C, and 250 °C for 21 days. Reaction products were characterized using bulk and clay-fraction XRD, XRF, and SEM–EDS, together with pre- and post-reaction fluid chemistry. At 80 °C, early dissolution of glauconite and other detrital components (K-feldspar, muscovite and calcite) was observed, resulting in increased concentrations of dissolved ions in the fluid but no authigenic clay formation. Authigenic smectite first developed at 150 °C, occurring primarily as grain-coating clay. With further heating to 200 °C, smectite began to transform into mixed-layer illite–smectite, accompanied by the first clear development of illite textures. At 250 °C, illitization advanced significantly, and the reacted products were dominated by wavy to fibrous illite. The resulting clay minerals and their grain-coating morphologies are comparable to coatings reported from buried sandstone reservoirs. These findings suggest that glauconite alteration can generate grain-coating clays that may help limit quartz cement growth and preserve porosity. However, the development of wavy/fibrous illite may also obstruct pore spaces and reduce permeability. Overall, glauconite-derived clay evolution may preserve porosity while still degrading permeability, and the net reservoir effect depends on the morphology and distribution (thickness and coverage) of the newly developed clay minerals. Full article

The recycling of acrylonitrile-butadiene-styrene (ABS) is crucial for a circular plastics economy, but repeated extrusion induces degradation that limits its reuse. This study establishes a comprehensive structure-property evolution mechanism for ABS 757K over five extrusion cycles and develops a novel image-recognition model for aging degree prediction. Multi-faceted characterization revealed that chain scission, oxidation of the polybutadiene (PB) phase, and the formation of chromophores led to progressive embrittlement, yellowing, and reduced thermal-oxidative stability. A key finding from Energy Dispersive Spectroscopy (EDS) was the stability and homogeneous distribution of sulfur-based antioxidants, which underpin the material’s superior resistance to degradation by effectively scavenging free radicals, which function as effective free radical scavengers. This mechanism underpins the material’s superior resistance to thermo-oxidative degradation. Consequently, significant molecular weight reduction and property deterioration were delayed until later extrusion cycles. Furthermore, a deep learning model based on the DeepLabV3+ architecture was trained to predict extrusion history directly from scanning electron microscopy (SEM) images of impact-fractured surfaces. The model achieved an average prediction accuracy exceeding 96.5%. Remarkably, it demonstrated excellent generalizability, maintaining high accuracy on two unseen commercial ABS grades. This indicates that the micro-morphological evolution pathway is a universal fingerprint of thermo-mechanical aging in ABS. This work not only elucidates the multi-scale degradation mechanism of recycled ABS but also provides a rapid, non-destructive tool for intelligent quality assessment in plastic recycling streams, bridging advanced machine learning with practical sustainability challenges. Full article

Background and Objectives: Head and neck cancers are heterogeneous malignancies with variable biological behavior and treatment response, contributing to high morbidity and mortality. Conventional imaging techniques are limited in their ability to capture tumor biology, highlighting the need for advanced functional imaging. This review aims to evaluate the role of multiparametric magnetic resonance imaging (MRI) in characterizing the tumor microenvironment. Materials and Methods: A narrative review was conducted based on a targeted literature search of databases, including PubMed and Google Scholar. Studies addressing advanced MRI techniques for assessing tumor cellularity, vascularity, molecular features, and oxygenation were selected and analyzed. Results: Perfusion techniques, such as dynamic contrast-enhanced MRI (DCE-MRI) and arterial spin labeling (ASL), provide a quantitative assessment of tumor vascularity and show value in predicting treatment response. Diffusion-based methods, including diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), enable evaluation of tissue cellularity and heterogeneity. Molecular approaches, such as chemical exchange saturation transfer (CEST) and amide proton transfer (APT), offer insights into protein content and proliferation. Oxygenation-sensitive techniques, such as blood oxygenation level dependent MRI (BOLD MRI) and oxygen-enhanced MRI (OE-MRI), allow non-invasive assessment of tumor hypoxia. Conclusions: Multiparametric MRI provides a comprehensive and biologically relevant evaluation of the tumor microenvironment in head and neck cancer, with potential to improve treatment prediction and support personalized therapeutic strategies. Full article

Mining activities generate substantial volumes of solid waste materials during exploration and processing. These residuals pose environmental and geotechnical concerns due to their large spatial footprints and associated risks but may also contain potentially valuable resources. These characteristics highlight the necessity and opportunity of effective management and monitoring strategies. In recent years, a diverse range of technologies and methods have been applied to characterize mine waste compositions and analyze their spatial–temporal variability. These include remote sensing systems, ground-based sensors, and advanced data-driven methods. Despite the rapid advancement, the existing literature provides limited insight into the critical evaluation of how these techniques are applied in practice. This review systematically examines peer-reviewed journal articles published between 2021 and 2024 to highlight the state of the art in characterization, modeling, and monitoring techniques for mine waste. The review identifies recent trends, key gaps, advantages, and limitations of these techniques. The summary suggests that mining companies and research communities are increasingly adopting innovative technologies, transitioning from conventional methods to more sustainable practices. However, it also reveals ongoing challenges and persistent limitations. Further efforts, such as real-time monitoring capabilities, are required to achieve full implementation and integration across the industry and academia. Full article

Background: Fragile X syndrome (FXS) is the most common monogenic cause of inherited intellectual disability and is primarily caused by CGG repeat expansion in the FMR1 gene. Conventional diagnostic methods have limited precision for sizing long repeat sequences and cannot resolve AGG interruptions, which are critical for comprehensive risk assessment. Existing national FXS reference materials are based on conventional methods and provide limited molecular information. Methods: We developed a targeted long-read sequencing assay for comprehensive FMR1 characterization, termed tLRS-FMR1, and applied it to a panel of 22 national FXS reference materials. Results: The tLRS-FMR1 assay demonstrated 100% concordance with standard methods while overcoming key limitations of conventional approaches. It enabled precise quantification of CGG repeat numbers, including full mutations (>200 repeats) that were only qualitatively reported by traditional techniques and provided comprehensive mapping of AGG interruption patterns. The assay showed high reproducibility, with 100% genotyping concordance across intra- and inter-assay replicates and achieved a detection limit of 3 ng/μL. Conclusions: This study successfully developed tLRS-FMR1 and established a new-generation national FXS reference material system with expanded molecular information and improved precision, providing a foundation for advancing the standardization and accuracy of FXS molecular diagnosis. Full article

Thin-film solar cells (TFSCs) remain a cornerstone of the global transition toward renewable energy, characterized by consistent reductions in manufacturing costs and steady gains in power conversion efficiency. In addition to electricity generation, TFSCs play an important role in advanced solar thermal cooling, heating, and energy storage systems, where their tunable optical absorption, low thermal mass, and flexibility enable integration with photovoltaic–thermal (PV/T) collectors, thermally driven cooling cycles, and hybrid thermal–electrical storage architectures. This paper provides a comprehensive review of prominent TFSC technologies, including copper indium gallium selenide (CIGS), cadmium telluride (CdTe/CdS), amorphous silicon (a-Si), copper zinc tin sulfide (CZTS), organic photovoltaics (OPVs), and metal halide perovskite solar cells (PSCs), with a focus on their material structures, performance specifications, and current efficiency benchmarks. Compared to state-of-the-art reviews, this article distinguishes itself by addressing next-generation innovations, cross-domain solar thermal–photovoltaic applications, and economic analysis. Specifically, the integration of machine learning and simulation-based material dynamics is examined to accelerate material discovery, process optimization, and the characterization of novel TFPV components relevant to coupled thermal–electrical energy systems. Furthermore, the study explores how additive manufacturing is transforming the industry through the development of high-efficiency electrodes, electrohydrodynamic atomization for thin-film deposition, and the fabrication of flexible solar arrays suitable for thermally integrated and building-scale energy systems, including space applications. By integrating advancements in module efficiency, scalable manufacturing approaches, and techno-economic analysis, this paper positions TFSCs as sustainable, resource-abundant technologies essential for next-generation solar thermal cooling, heating, and energy storage infrastructures. Full article