Search Results (310)

Achieving a favorable synergy of strength, ductility, and toughness is a critical challenge for expanding the engineering applications of titanium alloys. In this work, a medium-strength and high-toughness novel Ti-Al-Mo-V-Cr-Sn-Zr (named Ti62F) titanium alloy in the form of a Φ400 mm bar was adopted to systematically investigate the regulation behavior of double annealing on its microstructure and mechanical properties, and quantitative correlations between microstructural parameters and macroscopic properties were established. Increasing the cooling rate during the first annealing stage (air cooling, force air cooling and water quenching) significantly refined the secondary α (α_s) phase and reduced the volume fraction and size of the primary α (α_p) phase, leading to an increase in the ultimate tensile strength of the alloy from 1077 MPa to 1229 MPa. However, the impact-absorbed energy decreased from 51.5 J to 23.3 J. When the second annealing temperature was varied within the range of 625–675 °C, the ultimate tensile strength fluctuated slightly and the impact toughness increased moderately. Equiaxed α_p phase and relatively thick α_s can induce multiple crack deflections, prolong the crack propagation path and enhance energy absorption. Dislocations are mainly piled up at α/β phase boundaries, triggering void nucleation and growth, which dominate the ductility and toughness levels. Tensile twinning acts only as an auxiliary deformation mechanism and contributes limitedly to toughness. After heat treatment under the optimized schedule of 880 °C/2 h/AC + 650 °C/4 h/AC, the Ti62F alloy exhibits a superior strength–toughness balance compared with conventional medium-strength titanium alloys such as TA15, TC4, and TC4-DT. The findings can provide a heat treatment basis for microstructural regulation of large-size Ti62F bars and their engineering applications in aerospace structural components. Full article

Background/Objectives: Intramedullary tumors are uncommon spinal cord lesions that account for a small proportion of central nervous system neoplasms but are associated with a high risk of neurological morbidity. Accurate preoperative characterization is essential because therapeutic strategies, surgical planning, and functional prognosis depend strongly on tumor biology and growth behavior within the confined spinal cord environment. This study aims to characterize the radiological phenotype of intramedullary tumors and to identify imaging patterns that may assist in lesion characterization and diagnostic stratification. Methods: A retrospective analysis of preoperative MRI findings in patients with histopathologically confirmed intramedullary tumors was performed. Preoperative MRI examinations were systematically analyzed to describe imaging features according to tumor histology using conventional sequences (T1-weighted, T2-weighted, and contrast-enhanced imaging). Results: Distinct radiological phenotypes were observed across a wide spectrum of lesions. Glial tumors, including subependymoma, ependymoma, pilocytic astrocytoma, diffuse midline glioma H3K27M, glioblastoma, high-grade astrocytoma with piloid features, ganglioglioma, and diffuse leptomeningeal glioneural tumors, demonstrated variable combinations of cord expansion, margin definition, enhancement patterns, and tract involvement, reflecting differences between expansile and infiltrative growth. Secondary tumors such as metastases frequently exhibited aggressive imaging features, including extensive edema and intense or heterogeneous enhancement. Vascular lesions, including hemangioblastoma and cavernoma, showed characteristic vascular signatures, such as nodular enhancement with flow voids or susceptibility-related signal changes. Developmental lesions, such as epidermoid cysts, neurenteric cysts, and lipoma, displayed distinctive signal characteristics, especially on diffusion and T1, that aided differentiation from neoplastic processes. Conclusions: In conclusion, the structured radiological interpretation functions proposed herein are not only useful for diagnostic purposes, but could also be useful for risk stratification and therapeutic guidance. Full article

While aluminum (Al) continues to be a cornerstone for microelectronic interconnect technologies, its chronic tendency toward hillock growth and thermal instability necessitates a transition toward high-performance nanostructured material architectures. This research tackles these reliability bottlenecks by achieving a molecular-level integration of graphene nanoplatelets (GNPs) within Al matrices, a strategy designed to fortify structural resilience. Adopting a green chemistry approach, we synthesized Al-GNP (0.25 vol.%) composite thin films through Pulsed Laser Deposition (PLD) using precursors derived from recycled aluminum. A major obstacle—the formation of the deleterious Al₄C₃ intermetallic phase—was effectively suppressed by ensuring a homogeneous supramolecular dispersion via a specialized dual protocol (ultrasonication and magnetic stirring) during the powder metallurgy stage. Comprehensive physicochemical characterization, utilizing HR-TEM and XRD, verified the structural integrity of the multilayer GNPs (d-spacing = 4.6 Å). Furthermore, surface metrology analysis uncovered a radical shift in growth kinetics: whereas pure Al grew via a “spiky” Volmer-Weber mechanism (Sku = 31.17), the carbon-based inclusion stabilized the film evolution, tempering the kurtosis to Sku = 7.74. Analytical cross-sectional EDS confirmed both stoichiometric fidelity and the achievement of void-free Si/Pt/Al-GNP interfaces. These outcomes prove that a precise nanoscale tailoring of surface morphology via carbonaceous reinforcements significantly bolsters microstructural stamina. Consequently, these PLD-deposited composites emerge as sustainable, cutting-edge candidates for the next generation of microelectronic packaging and interfacial chemistry applications. Full article

Cu electroplating is one of the most expensive, complex and critical steps in fabricating through-glass vias (TGVs), which serve as the core component of 2.5D or 3D integration. This paper presents a simplified 2D via electroplating model to systematically investigate the influences of electrolyte additive, current density, and via geometry on plating performance in terms of via filling profile and Cu thickness. Under a fixed accelerator concentration of 0.1 mol/m³, plating performance for both blind- and through-vias initially improves but subsequently deteriorates with increasing suppressor concentration. Notably, the through-via filling mode dramatically transitions from super-conformal to sub-conformal, achieving a maximum throwing power (TP) of 135.74%. A gradual growth in current density from 0.1 to 0.3 amps/dm² (ASD) leads to deteriorating plating quality for both via types, with the through-via TP dropping to 95.56%. In addition, sub-conformal filling occurs in U-shaped, V-shaped, and X-shaped blind-vias if single-sided plating is employed. However, after shifting them to a through configuration with double-sided plating, complete filling can be realized across all cases. These findings offer a theoretical foundation and practical guidance for enhancing the depositing rate and minimizing/eliminating internal void for the Cu electroplating of TGVs. Full article

The crystallinity of cubic silicon carbide (3C-SiC) epilayers is improved through the use of a novel wafer bonding and regrowth technique resulting in a reduction in planar defects. The process involves the epitaxial growth of a 3–6 µm thick 3C-SiC seed on silicon (Si), which is polished and bonded to a new handle wafer before the original substrate and defective interface region of the 3C-SiC epilayer are removed. Further epitaxial growth on this Bonded Switchback template results in higher quality 3C-SiC epilayers through the reduction in crystal mosaicity, stacking fault defects, and elimination of interface voids. The process could be applied to 3C-SiC grown on both on- and off-axis substrates, and the form of the new handle has no impact on the growth process, enabling this technology to be applied to sapphire or hexagonal 4H-SiC substrates. The use of such substrates would overcome the thermal budget limitations of Si substrates for 3C-SiC heteroepitaxy and ion implantation. Bonded Switchback can improve material quality for applications in power electronics, as well as see the heterogeneous integration of 3C-SiC into other device structures, potentially leading to a new range of hybrid 3C-SiC/Si devices without the high density of defects observed at the interface between these two materials. Full article

Hydrodynamic efficiency in wetland systems is governed by the complex interaction between fluid flow and vegetation density. This study quantifies the impact of seasonal emergent vegetation growth on solute transport in a V-shaped flume. Using high-resolution tracer data from high-density (January) and low-density (November) conditions, we characterized hydraulic parameters, longitudinal velocity (v), and dispersion (D), across an upstream conduit (Reach 1) and a downstream retention zone (Reach 2). Results revealed that in January, Reach 2 exhibited massive hydraulic retardation (v ≈ 1.8 cm s⁻¹) and extensive non-Fickian tailing (variance > 30,000 s²), maintaining an idealized retentive state (Pe ≈ 20). Conversely, seasonal biomass reduction in November resulted in lower variance (≈16,500 s²) and drastically increased the risk of extreme advective bypass (Pe > 500). These findings provide critical empirical validation for macro-scale models like the Dynamic Model for Stormwater Treatment Areas (DMSTAs). Specifically, the massive temporal variance observed during the retentive state yielded an empirical Tanks-in-Series value of N ≈ 5.7, directly validating standard DMSTA defaults for dense emergent marshes. Furthermore, the Transient Storage Model (TSM) storage ratio (As/A) offers a quantitative mechanism to penalize modeled void fractions, accounting for vegetative “dead zones.” By integrating these flume-derived metrics, wetland managers can optimize hydraulic designs and improve the prediction of treatment efficiency across seasonal variations. Full article

Remote sensing change detection (RSCD), a fundamental task in Earth observation, aims to automatically identify land-cover changes (e.g., building construction, vegetation degradation) by comparing multitemporal satellite or aerial images of the same region. With the explosive growth of high-resolution remote sensing data, achieving real-time accurate change detection on edge computing devices (e.g., drone-embedded chips, satellite on-board processors) has become an urgent challenge—existing deep learning methods, despite high accuracy, are hindered by massive parameters and computational costs that preclude deployment on resource-constrained embedded hardware. To address this, we focus on lightweight (i.e., low parameter count and low computational cost) RSCD network design, targeting three critical bottlenecks: blurred boundaries of changed regions, missed detection of small objects, and insufficient computational efficiency. We propose ATCFNet (Adjacent-Temporal Cross Fusion Network), featuring a three-step progressive feature optimization strategy: (1) the Adjacent Feature Aggregation Module (AFAM) enhances shallow geometric details via lateral three-stage fusion to compensate for lightweight backbones; (2) the Temporal Attention Cross Module (TACM) integrates cross-level feature propagation and Convolutional Block Attention Module (CBAM) for collaborative optimization of high-level semantics and low-level details; and (3) the Efficient Guidance Module (EGM) establishes long-range dependencies using shared change priors and lightweight self-attention to suppress internal voids in changed regions. Experiments on three public datasets (LEVIR-CD, HRCUS, SYSU-ChangeDet) demonstrate that ATCFNet achieves state-of-the-art accuracy with merely 3.71 million (M) parameters and 3.0 billion (G) floating-point operations (FLOPs)—F1-scores of 91.46%, 77.05%, and 83.53%, significantly outperforming 18 existing methods in most indicators. Notably, it excels in edge integrity (avoiding jagged blurring at change boundaries) and small-target detection in high-resolution urban scenes. This study provides an efficient and reliable lightweight solution for edge computing scenarios such as real-time drone inspection and satellite on-board intelligent processing. Full article

This study conducts multi-scale numerical simulations spanning atomic to macroscopic scales (i.e., from nanometer to millimeter scale) to investigate the fatigue crack propagation behavior in the welded heat-affected zone (HAZ) of AH36 shipbuilding steel. A coupled molecular dynamics–finite element method (MD-FEM) was employed to establish a multi-scale model. Through the transfer of boundary displacements, equivalent mapping of crack morphology, and crack-tip tracking, an iterative multi-scale simulation of 600 tension–tension fatigue cycles was achieved. The results indicate that the crack propagation rate is significantly influenced by crack tip morphology (blunting/sharpening) and growth direction. Notably, the peak strain at the boundary is not the sole determining factor. Periodic blunting of the crack tip occurs during cyclic loading, accompanied by a decrease in the propagation rate. Additionally, the stress field near the crack tip induces microscopic defects such as voids in the nearby area, affecting the crack propagation. This study, based on multi-scale analysis, reveals the microscopic mechanism and evolution law of fatigue crack propagation in the heat-affected zone of AH36 steel welds. Full article

We propose a reaction–diffusion phase-field model to simulate the microstructure evolution of voids in systems with low vacancy concentration under irradiation. In this model, void growth and shrinkage are governed by reactions between vacancies/interstitials and the void surface, while an order parameter is introduced to describe void morphology. By avoiding the sharp increase in vacancy concentration near the void interface, the model enables the simulation of void evolution in low vacancy concentration matrices over enlarged time scales. When combined with classical nucleation theory, the approach enables quantitative, accurate three-dimensional simulations of slow void evolution processes, achieving comparability with rate theory models. Numerical results demonstrate that the model accurately captures the evolution of voids under dilution conditions. At the same time, its inherent scalability makes it broadly applicable to other material systems characterized by low solute concentrations. Full article

Lanthanum silicate oxyapatite (LSO) is a promising oxide ion conductor for low-temperature-operating electrochemical devices owing to its high ionic conductivity along the c-axis. However, the fabrication of thin films with controlled crystallographic orientation remains challenging. In this study, polymer-assisted deposition (PAD), a solution-based technique offering precise microstructural and compositional control, was employed to fabricate c-axis-oriented LSO thin films. The fabrication of undoped LSO and the effects of Al and Mg incorporation on its microstructure, orientation, and ionic conductivity were systematically investigated. Undoped LSO thin films crystallised with a preferential c-axis orientation in the annealing temperature range of 800 and 1100 °C, and scanning transmission electron microscopy observations revealed a highly crystalline, void-free microstructure. Upon annealing at 1200 °C, the undoped LSO exhibited columnar grains with anisotropic in-plane grain growth, whereas Al- or Mg-doped LSO suppressed anisotropic in-plane grain growth and retained an out-of-plane c-axis orientation. The undoped LSO showed higher in-plane ionic conductivity than the doped thin films, consistent with their distinct crystallographic orientations. These results demonstrate that PAD provides a viable pathway for tailoring the microstructure and the composition of LSO thin films, thereby facilitating their applications in solid oxide electrochemical devices. Full article

Aligned CS/Rx aerogels were fabricated by inducing non-directional ice growth (freeze-molding) followed by low-temperature curing, resulting in monoliths with interconnected channels, a high void fraction, and moldability. The swelling index (S%) was calculated to be 1029, the apparent density 0.496 g·cm⁻³, and the estimated porosity 90% based on micrographic analysis. Aerogels have mechanical behavior Shore A hardness greater than 25. Batch metal removal tests were performed (10 mL, 100 mg·L⁻¹ Cr(VI), 0.19 g adsorbent, 24 h, and pH 5–5.5), and the material achieved 95% metal removal. Additional kinetic and isothermal results were obtained using CS85R15 on a packed column (20 to 140 mg·L⁻¹, 1000 mL Cr(VI), 0.80 g adsorbent, 24 h, and pH 5–5.5). Equilibrium data were consistent with a heterogeneous surface hosting a specific site, as reflected in the joint Freundlich/Langmuir fit (q_max 100.8 mg·g⁻¹ for Langmuir). This confirmed the preservation of chitosan functionalities (–OH/–NH) after processing, while XPS detected chromium on the surface with signals consistent with the partial reduction of Cr(VI) to Cr(III) on the aerogel surface. This highlights the relevance of adsorption-based technologies for water remediation, where high-porosity and low-density materials allow for short diffusion pathways and capture electrostatics by protonated amines and redox conversion of hazardous substances. The soft-cure freeze-molding technique is simple, scalable, and compatible with packed-bed/column operation, providing a material platform for tailoring the microstructure (sheets and channels) and surface chemistry to regenerable sorbents for industrial wastewater treatment. Full article

This review focuses on electromagnetic imaging methods widely used in urban geophysics and civil engineering. The rapid growth of the urban population and the increase in the frequency of extreme events related to climate change make novel approaches to the geophysical monitoring of urban areas and civil infrastructures essential in the context of programs for the sustainability and resilience of cities. In this scenario, there is a growing interest in using ground-based electromagnetic methods to investigate strategic infrastructures such as bridges, tunnels, dam embankments, power plants, energy plants and pipelines in a non-invasive way. The development of cost-effective, user-friendly sensor arrays, robust methodologies for tomographic data inversion, and AI-based and machine learning techniques has rapidly transformed these methods. This review critically analyzes the results relating to the application of ground-based electromagnetic methods in infrastructure monitoring and surveillance over the past 20 years by presenting a selection of best practice examples and studies planned to support programs for the resilience and maintenance of engineering infrastructures. The analysis reveals that these methods are highly effective in addressing a broad spectrum of monitoring issues in view of effective maintenance of civil infrastructures. In fact, these methods are essential for detecting the geometry of buried objects (e.g., bars and voids), enabling the early detection of degradation phenomena, and mapping water infiltration processes inside structures, as well as many other challenging applications. Finally, prospectives for development are identified in terms of using soft robot technologies, miniaturized sensors, and AI-based methods to acquire, process and interpret data as well as to design smart operational guidelines for infrastructure management. Full article

Satellite observations of methane are frequently compromised by extensive data gaps caused by cloud cover and aerosol contamination, limiting their utility for continuous regional monitoring. To reconstruct these spatiotemporal discontinuities, this study developed the Stacked Ensemble Reconstruction Framework for Methane (SERF-XCH₄). By integrating Sentinel-5P TROPOMI retrievals with 25 multi-source environmental covariates, we generated a spatiotemporally continuous, high-resolution (0.1°) monthly dataset (SERF-XCH₄-IM) for Inner Mongolia spanning 2019 to 2023. Comprehensive validation demonstrates that the framework achieves exceptional predictive fidelity with a Coefficient of Determination ($R^2$) of 0.93 and a Root Mean Square Error (RMSE) of 7.89 ppb, significantly surpassing the performance of individual base learners and traditional interpolation methods. Furthermore, spatial block cross-validation confirmed robust generalization capabilities ($R^2=0.90$) in data-void regions. To unravel the “black box” of the model, SHapley Additive exPlanations (SHAP) analysis was employed, revealing that temporal factors (contributing 63.9%), air temperature, and elevation are the dominant drivers governing XCH₄ variability. Spatiotemporal analysis further identified the Hulunbuir region as a significant growth “hotspot” with an annual increase rate exceeding 18.5 ppb/yr, a trend primarily driven by intensified emissions during the autumn and winter seasons. Consequently, this framework establishes a high-precision, interpretable paradigm for regional methane monitoring and geo-information reconstruction. Full article

Hydrogen embrittlement is known to adversely affect the mechanical properties of low-carbon steels used for pipelines and pressure vessels, leading to accelerated crack growth and lowered fracture toughness. To overcome the limitations of surface-based analysis, this study employs X-ray micro-computed tomography (µ-CT) to provide a comprehensive 3D evaluation of the crack evolution. This approach is used to assess hydrogen-assisted crack growth in P355NH compact tension samples from previous fracture mechanical tests and enables a precise quantification of the internal crack path and the crack tip opening angle (CTOA) across the entire specimen thickness as well as the local damage morphology. By integrating these spatial parameters, a deeper understanding of the impact of hydrogen on local fracture mechanisms is achieved, revealing insights that have remained hidden in previous two-dimensional microscopy observations. For instance, µ-CT results clearly demonstrate that the hydrogen-assisted crack propagation is associated with increased void formation and secondary cracking in vicinity of the crack tip. However, it is proposed that the results are superimposed with continuous hydrogen desorption, which implies a need for in situ charging during mechanical loading and an analysis of the hydrogen concentration profile. Both will be the scope of further studies. Full article

To address the limitation of insufficient mechanical strength and short service life in biodegradable bamboo fiber mulch film (BFM) replacing plastic film in agriculture, this study applied a biochemical method to make bamboo fiber and used bacterial cellulose (BC) as a natural nanoscale reinforcing agent to fabricate high-performance bacterial cellulose bamboo fiber mulch film (BC-BFM). The physical and mechanical properties, chemical structure, seed germination and degradation behavior performance of BC-BFM were characterized. Results demonstrated the structural compactness and homogeneity of the BC-BFM were improved markedly with the increase in BC addition and BC formed a 3D nanofibrillar network that effectively bridged inter-fiber voids. The tensile, burst and tear indexes of BC-BFM all significantly rose with BC addition. Notably, compared to plastic film and BFM, BC-BFM exhibited a good effect on mung bean seed germination and the best growth speed was at 5% BC addition. Furthermore, the degradation test showed that the degradation rate of BC-BFM within 90 d was three times less than that of BFM and service life was similar to plastic film. This showed that it was a promising method to prepare biodegradable high-quality BFM through biochemical preparation of bamboo fiber and BC nanocellulose reinforcement. This method markedly enhanced the mechanical performance and durability of BC-BFM, providing a feasible technical path for the development of biodegradable high-performance green agricultural covering materials with long service life. Full article