Search Results (1,216)

This study investigates the as-cast Mg-8Gd-1Y-2Sm-1.2Zn-0.5Mn (wt.%) alloy with high rare-earth content. Solution treatments were conducted at 480 °C, 520 °C, and 560 °C for 6–10 h. Microstructure and mechanical properties were characterized using OM, XRD, SEM-EDS, and compression testing. The as-cast alloy shows a dendritic structure with continuous grain-boundary phases (Mg₅RE, W, and LPSO), exhibiting a compressive yield strength of 145 MPa, ultimate strength of 238 MPa, and fracture strain of 12.66%. Solution temperature has a critical influence on phase dissolution and grain refinement. Notably, the overall plasticity of the material did not show a significant dependence on the specific solution temperature or holding time within the studied range. Treatment at 520 °C produces the most balanced microstructure: clear grain boundaries, extensive phase dissolution, refined grains, and enhanced solid-solution strengthening. Specifically, 520 °C for 10 h results in the finest and most uniformly distributed residual phases, a homogeneous matrix, the highest compressive strength, and suitable conditions for subsequent aging, thus being identified as optimal. Fractography reveals a transition from quasi-cleavage in the as-cast state toward enhanced ductility after solution treatment. However, small cleavage facets after 10 h are attributed to stress concentrations from rare-earth-rich regions and reduced deformation compatibility due to retained LPSO phases. Full article

The solid structure of industrial sinter comprises seven mineral associations (A, B, C, D, Ds, E, N) which have different relative abundances of key minerals, textures and spatial relationships to micro-macropores and hematite nuclei. Among the key characteristics of the mineral associations: (MA), MA-A comprises abundant SFCA-I microplates with hematite; MA-B consists of disseminated fine-grained magnetite in a network of SFCA-III microplates; MA-C is similar to MA-B but contains patches of dendritic SFCA-III with larnite and minor glass; MA-D comprises magnetite surrounded by coarse prisms of SFCA within glass; MA-Ds, a subtype of MA-D, includes SFCA with secondary skeletal hematite; MA-E consists of anhedral to skeletal magnetite or hematite in a matrix of glass; and MA-N comprises unmelted hematite nuclei from iron ore feedstock. SFCA-III and SFCA-I are dominant in MA-B and MA-A, respectively, whilst magnetite is the most common mineral in MA-C, MA-D/Ds and MA-E. Low-temperature sintering samples are largely of MA-A to MA-D (62 area %), which contain higher combined levels of SFCA-SFCA-III and lower levels of magnetite-dominant MA-E (12.6 area %), whereas high-temperature/magnetite sintering examples had high levels of magnetite-dominant MA-E (31.6 area %) and MA-D/Ds (52.1 area %) and low levels of MA-A to MA-C (8.9 area %). It is proposed that the formation of each MA is controlled by the peak sintering temperature attained, the dwell time at higher temperature which adversely allows fractional crystallisation to tie up more Fe in magnetite rather than forming SFCA phases during cooling, and especially a slower rate of cooling which promotes the formation of more SFCA family phases at lower temperatures. However, local variations in chemistry inherited from raw material granulation and assimilation during sintering of Si-rich gangue or ore nuclei are also important. Full article

A four-compartment tumor–immune interaction model is studied in a belief-based uncertain framework. The deterministic dynamics for tumor cells, natural killer cells, dendritic cells, and cytotoxic CD8${}^{+}$ T lymphocytes are extended to an uncertain differential system driven by a canonical Liu process, with therapeutic effects represented through treatment-related parameters acting on the respective populations. The analysis establishes well-posedness in the biologically relevant positive orthant under structural conditions compatible with the model nonlinearities, and it characterizes stability properties in the sense appropriate to uncertain dynamical systems. Sufficient conditions are derived for the existence of a global attracting set describing the long-time behavior of trajectories. The analytical results are complemented by numerical experiments based on $\alpha$-path dynamics to illustrate uncertainty-aware therapeutic scenarios and to connect the qualitative theory with observable system behavior. Full article

Through the mechanical analysis of AlCoCrFeNi thin-walled high-entropy alloy materials fabricated by plasma arc additive manufacturing, this study examines the practical application prospects of plasma arc manufacturing technology for thin-walled high-entropy alloys and explores its future development directions. Using a plasma arc oscillation process, a 50-layer fine additive experiment was conducted on AlCoCrFeNi high-entropy alloy materials employing both reciprocating and layer-by-layer accumulation methods. The samples were analyzed for overall appearance, microstructure, hardness, and tensile properties. The results indicate that the proportions of columnar and intergranular dendrites in the thin-walled high-entropy alloy specimens are similar, and the columnar dendrites exhibit a uniformly sized cross shape. The variation in Vickers microhardness along the horizontal direction shows lower strength at the edge positions, gradually increasing with horizontal distance. A comparison of the alloy’s transverse and longitudinal tensile specimens revealed that samples parallel to the deposition direction exhibit more regular structural arrangements, while specimens perpendicular to the deposition direction show unavoidable stress concentration at the deposition sites during tensile testing. With the increase in the height of the longitudinal specimens, the FCC structures in the alloy are significantly refined, the organizational arrangement becomes more regular, and the elongation increases. This study elucidates the plasma arc preparation technique for thin-walled high-entropy alloy materials, which is expected to achieve precise control over material composition, accurate observation of grain refinement, and uniform distribution of Vickers hardness, thereby enhancing the mechanical properties and thermal stability of the materials, with promising applications in aerospace, energy, and industrial fields. Full article

Zinc dendrite growth and side reactions remain critical challenges hindering the advancement of aqueous zinc-ion batteries (AZIBs). This study proposes a gel-based strategy for designing high-performance separators by regulating the crystal morphology of the metal–organic framework UiO-66 within a cellulose nanofiber (CNF) gel matrix. The resulting gel-derived separators exhibit distinctive structural and interfacial properties that significantly enhance battery performance. Compared with hierarchical porous structures (H-UiO-66), the octahedral morphology (O-UiO-66) disperses more uniformly in the CNF gel network, forming well-defined ion transport channels through its integrated gel architecture. The fabricated O-UiO-66/CNF gel separator demonstrates exceptional hydrophilicity (contact angle 21°), high porosity (73.2%), and significantly improved zinc ion migration number (0.72). Electrochemical tests reveal that this gel-based separator effectively guides uniform zinc deposition while suppressing dendrite growth. Zn/Zn symmetric cells using the O-UiO-66/CNF gel separator achieve a cycle life exceeding 800 h at 1 mA cm⁻². The Zn/MnO₂ full cell maintains 98.1% capacity retention after 100 cycles at 1 A g⁻¹. This work establishes a structure–performance relationship between MOF morphology and gel separator properties, providing new insights for designing advanced gel-based materials for AZIBs. Full article

Lithium–sulfur (Li-S) batteries promise high energy density and low cost but are hindered by polysulfide shuttling, sluggish redox kinetics, poor sulfur conductivity, and lithium dendrite formation. Here, a targeted cation-substitution strategy is applied to Co₃O₄ spinels by replacing octahedral Co³⁺ sites with trivalent Al³⁺ or Fe³⁺, generating Al₂CoO₄ and Fe₂CoO₄ with exclusively tetrahedral Co²⁺ sites. Structural characterizations confirm the reconstructed cationic environments, and electrochemical analyses show that both substituted spinels surpass pristine Co₃O₄ in LiPS adsorption and catalytic activity, with Al₂CoO₄ delivering the strongest LiPS binding, fastest Li⁺ transport, and most efficient redox conversion. As a result, Li-S cells equipped with Al₂CoO₄-modified separators exhibit an initial capacity of 1327.5 mAh g⁻¹ at 0.1C, maintain 883.3 mAh g⁻¹ after 200 cycles, and deliver 958.6 mAh g⁻¹ at 1C with an ultralow decay rate of 0.034% per cycle over 1000 cycles. These findings demonstrate that selective Co-site substitution effectively tailors spinel chemistry to boost polysulfide conversion kinetics, ion transport, and long-term cycling stability in high-performance Li-S batteries. Full article

Metal oxide nanomaterials have emerged as transformative materials in the quest to enhance the energy density and overall performance of lithium-ion batteries (LIBs) and solid-state batteries (SSBs). Their unique properties—including their large surface areas and short ion diffusion pathways—make them ideal for next-generation energy storage technologies. In LIBs, the high surface-to-volume ratio of metal oxide nanomaterials significantly enlarges the active interfacial area and shortens the lithium-ion diffusion paths, leading to an improved high-rate performance and enhanced energy density. Transition metal oxides (TMOs) such as nickel oxide (NiO), copper oxide (CuO), and zinc oxide (ZnO) have demonstrated significant theoretical capacities, while binary systems like NiCuO offer further improvements in cycling stability and energy output. Additionally, layered lithium-based TMOs, particularly those incorporating nickel, cobalt, and manganese, have shown remarkable promise in achieving high specific capacities and long-term stability. The synergistic integration of metal oxides with carbon-based nanostructures, such as carbon nanotubes (CNTs), enhances the electrical conductivity and structural durability further, leading to a superior electrochemical performance in LIBs. In SSBs, the use of oxide-based solid electrolytes like garnet-type Li₇La₃Zr₂O₁₂ (LLZO) and sulfide-based electrolytes has facilitated the development of high-energy-density systems with excellent ionic conductivity and chemical stability. However, challenges such as high interfacial resistance at the electrode–electrolyte interface persist. Strategies like the application of lithium niobate (LiNbO₃) coatings have been employed to enhance interfacial stability and maintain electrochemical integrity. Furthermore, two-dimensional (2D) metal oxide nanomaterials, owing to their high active surface areas and rapid ion transport, have demonstrated considerable potential to boost the performance of SSBs. Despite these advancements, several challenges remain. Morphological optimization of nanomaterials, improved interface engineering to reduce the interfacial resistance, and solutions to address dendrite formation and mechanical degradation are critical to achieving the full potential of these materials. Full article

Nickel–Aluminum–Bronze (NAB) has gained significant attention in marine applications due to its excellent corrosion resistance and has shown growing potential for laser powder bed fusion (L-PBF) additive manufacturing. However, research on the fabrication of NAB alloys using L-PBF remains relatively limited. In this study, fully dense NAB samples were successfully fabricated through L-PBF process parameter optimization. The microstructural evolution and mechanical properties of both as-built and annealed L-PBF samples were systematically investigated and compared with those of traditionally cast NAB. The results reveal that the as-built L-PBF specimens primarily consist of columnar β′ grains, with the α phase distributed along the grain boundaries and a small amount of κ phase precipitated within the β′ matrix, distinctly different from the cast microstructure characterized by a columnar α-phase matrix with precipitated β′ and κ phases. After annealing at 675 °C for 6 h, the β′ phase in both methods decomposed into α + κ phases, and the original columnar structure in the L-PBF specimens transformed into a dendritic morphology. Compared to the cast samples, the L-PBF-produced NAB alloy exhibited significantly enhanced yield strength, tensile strength, and microhardness, attributable to rapid solidification during the L-PBF process. Following annealing, the yield strength and elongation increased by 12.8% and 184.4%, respectively, compared to the as-built condition, resulting from the decomposition of the martensitic phase into α + κ phases and further grain refinement. Full article

Fractal geometry offers a mathematical framework to quantify the complexity of brain structure and function. The fractal dimension (FD) captures self-similarity and irregularity across spatial and temporal scales, surpassing the limits of traditional Euclidean metrics. In neuroscience, FD serves as a key descriptor of the brain’s hierarchical organization—from dendritic arborization and cortical folding to neural dynamics measured by diverse neuroimaging techniques. This review summarizes theoretical foundations and methodological advances in FD estimation, including the box-counting approach for imaging, and Higuchi’s and Katz’s algorithms for electrophysiological data, addressing reliability and reproducibility issues. In addition, we illustrate how fractal analysis characterizes brain complexity in health and disease. Clinical applications include detecting white matter alterations in multiple sclerosis, atypical maturation in intrauterine growth restriction, reduced cortical complexity in Alzheimer’s disease, and altered neuroimaging patterns in schizophrenia. Emerging evidence highlights FD’s potential for distinguishing consciousness states and quantifying neural integration and differentiation. Bridging mathematics, physics, and neuroscience, fractal analysis provides a quantitative lens on the brain’s multiscale organization and pathological deviations. FD thus stands as both a theoretical descriptor and a translational biomarker whose standardization could advance precision diagnostics and understanding of neural dynamics. Full article

Epstein-Barr virus (EBV) infection shows the strongest causative association with multiple sclerosis (MS), but its contribution to disease progression and the mechanisms allowing for viral persistence in the MS brain are still elusive. Studies in post-mortem MS brain tissue indicate an ongoing yet ineffective antiviral immune reaction in advanced stages of the disease. EBV has evolved strategies to evade immune recognition and clearance by the host immune system during both the latency and lytic phase of its life cycle. Recent evidence demonstrates that cells expressing EBV latent membrane protein (LMP) 2A exploit the PD-1/PDL1 inhibitory immune checkpoint to escape immune surveillance and maintain a persistent latent infection in the MS brain. This study investigated whether the virus also utilizes this inhibitory mechanism during other phases of the viral life cycle. By using multiple immunostainings on highly inflamed MS brain tissues containing meningeal tertiary lymphoid structures (TLSs), we analyzed PD-L1 expression on EBV-infected cells expressing EBNA2, five EBV lytic gene products, BZLF1, BHRF1, BMRF1, BALF2, and gp350/220, as well as on follicular dendritic cells within the TLSs. This is the first study describing in secondary progressive MS brain tissue the expression and the cellular and tissue distribution of PD-L1 on EBV-infected cells being in different stages of the viral life cycle, and confirms the meningeal TLSs as immune-permissive habitats favoring the maintenance of an intracerebral EBV reservoir. Full article

The accurate determination of trace metals in aqueous matrices necessitates robust sample preparation techniques that enable selective preconcentration of analytes while ensuring compatibility with subsequent instrumental analysis. Dispersive solid-phase extraction (d-SPE), a suspension-based variant of conventional solid-phase extraction (SPE), facilitates rapid sorbent–analyte interactions and enhances mass transfer efficiency through direct dispersion of the sorbent in the sample solution. This approach offers significant advantages over traditional column-based SPE, including faster extraction kinetics and greater operational simplicity. When supported by appropriately engineered sorbents, d-SPE exhibits considerable potential for the selective enrichment of trace metal analytes from complex aqueous matrices. In this work, a fibrous silica-based chelating material, DSA-KCC-1, was synthesized by grafting 3,5-Di-tert-butylsalicylaldehyde (DSA) onto aminopropyl-modified KCC-1. The dendritic KCC-1 scaffold enables fast dispersion and short diffusion pathways, while the immobilized phenolate–imine ligand introduces defined binding sites for transition-metal uptake. Characterization by FTIR, TGA, BET, FESEM/TEM, XRD, and elemental analysis confirmed the successfulness of functionalization and preservation of the fibrous mesostructured. Adsorption studies demonstrated chemisorption-driven interactions for Pb(II) and Co(II) from water, with Langmuir-type monolayer uptake and pseudo-second-order kinetic behavior. The nano-adsorbent exhibited a markedly higher affinity for Pb(II) than for Co(II), with maximum adsorption capacities of 99.73 and 66.26 mg g⁻¹, respectively. Integration of the DSA-KCC-1 nanosorbent into a d-SPE–ICP-OES workflow enabled the reliable determination of trace levels of the target ions, delivering low limits of detection, wide linear calibration ranges, and stable performance over repeated extraction cycles. Analysis of NIST CRM 1643d yielded results in good agreement with the certified values, while the method demonstrated high tolerance toward common coexisting ions. The combined structural features of the KCC-1 support and the Schiff-base ligand indicate the suitability of DSA-KCC-1 for d-SPE workflows and demonstrate the potential of this SPE format for selective preconcentration of trace metal ions in aqueous matrices. Full article

To ensure reliable and accurate short-term photovoltaic power generation prediction, this study introduces an integrated forecasting framework that combines the gradient boosting paradigm with a dendritic neural structure, termed Gradient Boosting Multi-Bias Dendritic Units Integrated in a Fully Connected Neural Network (GBMDF). The proposed GBMDF algorithm minimizes prediction deviations by progressively capturing the nonlinear mappings between residual predictions and environmental variables through an iterative error-correction process. Compared with traditional data-driven learning algorithms, GBMDF can comprehensively utilize multiple meteorological inputs while maintaining strong interpretability and analytical transparency. Furthermore, leveraging the flexibility of the GBMDF, the prediction accuracy of existing models is improved through a proposed compensation enhancement technique. Under this mechanism, GBMDF is trained to offset the residual differences in alternative predictors by examining the correlations between the error patterns of alternative predictors and weather attributes. This enhancement method features a simple concept and effective practical performance. Validation experiments confirm that GBMDF not only achieves higher accuracy in photovoltaic output prediction but also improves the overall efficiency of other forecasting methods. Full article

CeO₂ is a crucial functional material in catalysis and energy applications, whose performance is highly morphology-dependent. Traditional synthesis methods often rely on organic templates or surfactants, which complicate the processes and pose environmental concerns. This study introduces an eco-friendly approach utilizing a methanol–water (MeOH-H₂O) mixed solvent system combined with NH₄HCO₃ to achieve controllable synthesis of multi-morphology CeO₂ without surfactants or templates. The effects of different solvent systems (pure H₂O, pure MeOH, and their mixtures) and NH₄HCO₃ as an inexpensive regulator on precursor phase behavior and crystallization were systematically investigated. By optimizing the Ce:N molar ratios (1:1 to 1:7) as well as reaction times (0.5 to 36 h), our findings indicate that H₂O significantly enhances crystallinity (from 40.9% to 61.4% for precursors, reaching 70.3% after calcination) and promotes octahedra formation in the MeOH-H₂O mixed system, while NH₄HCO₃ acts as a structure-directing agent to control size (e.g., ~240 nm octahedra at Ce:N = 1:1, up to 375 nm at Ce:N = 1:2) and partially substitutes for high-temperature calcination in improving crystallinity. Variety morphologies, including plates, dendrites, octahedra, and hollow structures, were successfully synthesized. This work elucidates the synergistic mechanism by which solvents and NH₄HCO₃ influence CeO₂ nucleation and growth, thereby providing an environmentally friendly synthesis route with significant potential applications in catalysis and energy storage. Full article

Zinc-ion batteries (ZIBs) are regarded as one of the promising next-generation energy storage technologies due to their high volumetric capacity, cost-effectiveness, and high safety. MXene materials, featuring a unique two-dimensional (2D) layered structure, excellent conductivity, and tunable surface chemistry, have been widely applied in energy storage systems. This review summarizes the recent progress in experimental and computational strategies for MXene-based ZIBs. The construction of MXene-based electrodes and the effect mechanisms of Zn-ion transport facilitation, electrode cycling stability, and anode dendrite suppression are discussed. Subsequently, the theoretical simulation strategies for MXene performance investigation are analyzed, including surface chemistry and defect engineering of MXene-based electrodes and the rational design of heterostructure interfaces for enhancing conductivity and suppressing Zn dendrite growth. Finally, the review outlines the major challenges that currently hinder the applications of MXene in ZIBs and proposes future research directions, offering insights that may guide the continued advancement of next-generation MXene-based energy storage systems. Full article

The typical microstructure and mechanical properties of twin-roll cast (TRC) 2139 aluminum alloy were investigated and compared with mold casting (MC) 2139 alloy. This work pioneers the application of TRC to produce 2139 Al-Cu-Mg alloy, a material that is challenging for rapid solidification. The TRC process resulted in a denser dendritic structure, with the composition of intermetallic compounds, primarily Al₂Cu and Al₂CuMg, remaining largely stable throughout the casting process. After solution treatment, the recrystallized grains in the MC sheets were uniformly distributed, while the TRC sheets exhibited a more localized and refined recrystallized microstructure, particularly within coarse second-phase regions. Following heat treatments, the TRC sheets showed a significant increase in the Ω phase after T6, with a slight growth in size and a uniform distribution, while the Ω phase in T8 showed an increased density and smaller size, which diffused evenly across the material. The TRC process uniquely refines the microstructure and enhances Ω phase precipitation, yielding a 10%+ improvement in strength and ductility over conventional casting. The mechanical properties of the TRC sheets improved significantly: tensile and yield strengths increased by over 10% after T6, compared to MC sheets, with elongation slightly higher in TRC. T8 treatment further enhanced the mechanical properties of the TRC sheets, achieving an improvement in strength with only a minor trade-off in elongation. This establishes TRC as a superior industrial route for high-performance aluminum sheets, offering a promising industrial route, delivering substantial improvements in both strength and ductility over conventional casting methods. Full article