Search Results (1,044)

In the field of material micro-/nano-analysis, the lack of an efficient method for characterizing the same microregion has been an obstacle in scientific research. This not only severely affects the efficiency and depth of academic communication, but also creates loopholes for data manipulation. To address these challenges, it is essential to develop microscale repositioning techniques to achieve repeatable characterization. However, microscale localization techniques based on Transmission Electron Microscopy (TEM) remain underdeveloped, facing issues such as poor localization accuracy, high costs, and cumbersome procedures in practical applications. This paper proposes a positioning method for nanoscale samples that utilizes coordinate grids and artificially added micron-scale markers as references. Accurate localization and retrieval of micro- and nanoscale targets in TEM were achieved using a confined comparison approach. This method is simple, cost-effective, and universally applicable to Inter-instrument correlative operation, enabling repeated characterization of the same microregion. It is also effective in Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). By enhancing the integration efficiency between TEM, SEM, and AFM, this method will yield more meaningful data and address challenges such as target localization difficulties and poor data reproducibility. It will mitigate issues related to data fabrication and experimental irreproducibility, thereby offering technical support for the smooth progress of research and academic exchange activities. Full article

Fused filament fabrication of thermoplastic composites, despite its recyclability, increased strength, and efficiency, faces structural limitations under elevated temperatures. The literature on heat treatments for improving the thermal resilience of accessible 3D printed composites is limited. Therefore, this study comprehensively presents the efficacy of annealing on carbon fiber reinforced polyamide (PAHT-CF). The methodology includes uniaxial tensile testing of 200 samples across a wide temperature range (25–150 °C) and five different infill orientations, annealed as per the Technical Data Sheet (80 °C, 12 h). Scanning electron microscopy (SEM) of the fracture surfaces revealed the microstructural changes responsible for the improved properties after annealing. At 25 °C, annealing led to a 50% strength increase (63.88 MPa) and a 70% lower strain (2.65%). At 150 °C, the material maintained a 17.5% strength advantage (23.62 MPa) and a 17.5% reduction in strain (12.67%). The 0°, 90°, and 0/90° orientations exhibited the highest improvements, while the remainder displayed lower strengths and higher deformation beyond the glass transition temperature (70 °C). Overall, annealed PAHT-CF demonstrates high-temperature resilience, comparable to previously analyzed materials like carbon fiber reinforced polyether–ether–ketone (PEEK-CF). This makes it a potentially accessible alternative for the aerospace and automotive sectors. However, practical applications must consider the trade-off between its enhanced mechanical properties and the increased lead time from annealing. Full article

As the most commercially developed metal additive process, laser powder bed fusion (LPBF) is vital to advancing several industry sectors, enabling high-precision part production across aerospace, biomedical, and manufacturing industries. Al 7075 alloy offers low density and high-specific strength yet faces LPBF challenges such as hot cracking and porosity due to rapid solidification, thermal gradients, and a wide freezing range. To address these challenges, this study proposes an integrated computational and experimental framework to enhance the LPBF processability of Al 7xxx alloys by compositional modification. Using the Calculation of Phase Diagram approach, printable Al 7xxx compositions were designed by adding grain refiners (V and/or Ti) and a eutectic solidification enhancer (Mg) to Al 7075 alloy to enable grain refinement and eutectic solidification. Subsequent LPBF experiments and characterization tests, such as metallography (scanning electron microscopy), energy-dispersive X-ray spectroscopy, X-ray diffraction, and X-ray micro-computed tomography, confirmed the production of refined microstructures with reduced defects. This study contributes to existing approaches for producing high-quality Al 7xxx alloy parts without significant compositional deviations using an integrated computational and experimental approach. Finally, aligning with the Materials Genome Initiative, this study contributes to the development and industrial adoption of advanced materials. Full article

This study investigates an alternative methodology for incorporating polymeric and steel fibers into concrete. Conventional reinforcement approaches often require complex application techniques and face industrial limitations. In contrast, the present work evaluates the use of short, discontinuous fibers—commercial polypropylene fibers (PFRC), polypropylene fiber braid (PFBRC) and steel fibers (SFRC)—which enable improved dispersion, ease of mixing and potential mechanical benefits. The fibers were randomly oriented and evenly distributed within the cementitious matrix. Mechanical performance was assessed through four-point bending tests combined with displacement measurements, acoustic emission analysis and uniaxial compression tests, while scanning electron microscopy (SEM) confirmed fiber–matrix interaction and fragment retention. The results demonstrated significant improvements, with compressive strength exceeding that of unreinforced concrete, while hybrid fiber systems provided enhanced crack resistance and post-cracking stability. Overall, the findings highlight that the integration of discontinuous fibers may provide tangible mechanical advantages, potentially outweighing the structural benefits of continuous reinforcing bars in applications requiring high strength and reliable mechanical performance. Full article

The safeguarding and enhancement of historic buildings and artifacts in Italy’s inner areas are essential to protect their outstanding cultural value. However, these territories often face complex orographic and environmental conditions that make traditional surveying and documentation challenging. To address these issues, this study proposes a framework for the digitalization and virtual dissemination of architectural heritage aimed at supporting safe and sustainable tourism. The proposed approach integrates unmanned aerial vehicle (UAV) photogrammetry with laser scanning to produce three-dimensional models of historic structures. These digital models are then semantically enriched and simplified for use within a web-based virtual reality (VR) platform, enabling interactive learning experiences for increase cultural heritage accessibility. The framework is validated through the case study of the Roccapreturo Tower in Acciano (AQ), located in the inner areas of the Abruzzo region, a landscape characterized by high morphological complexity. Results demonstrate the effectiveness of drone photogrammetry in capturing detailed and accurate representations of cultural heritage assets while ensuring operational efficiency and accessibility. The resulting VR models promote heritage safeguarding and sustainable tourism, confirming the potential of UAV-based technologies in the digital transformation of cultural heritage. Full article

Green synthesis methods of silver nanoparticles have gained great attention because they offer sustainable, eco-friendly, and less-toxic alternatives to traditional methods. This study sheds light on the green synthesis of chitosan silver nanoparticle composites, providing a comparative evaluation of microwave-assisted (M1) and a one-pot (M2) reduction methods. The morphological, crystallinity, and structural uniformity characteristics were evaluated by UV-Visible, Raman spectroscopy, X-ray diffraction (XRD) and scanning electron microscopy (SEM) with employing image processing pipeline based on deep learning model for segmentation and particles size estimation. The UV-visible spectrum exhibited independent SPR peaks ranging from 400 to 450 nm for all samples; however, microwave assisted-synthesis possessed narrower and more intense peaks indicative of better crystallinity and mono-dispersity. SEM depicted smaller, more uniformly dispersed particles for microwave-assisted (M1), while deep learning segmentation showed lower particle size variability (σ ≈ 24–43 nm), compared to polydisperse (σ ≈ 16–59 nm) in M2 samples. XRD showed crystalline face-centered cubic (FCC) silver with dominant peaks in M1 samples, whereas M2 had broader, less intense peaks with amorphous features. Raman vibrations revealed more structural order and homogenous capping in M1 than M2. Therefore, microwave-assisted (M1) showed better control on nucleation, particle size, crystallinity, and homogeneity due to a faster and uniform energy distribution. The future research would focus on the antimicrobial evaluation of such nanoparticles in agronomy. Full article

Efficient water management for irrigation is critical for sustaining plant production in arid and hyper-arid regions, where optimizing emitter type, burial depth, and irrigation scheduling can significantly enhance water-use efficiency and yield. This study evaluated the effects of continuous and intermittent subsurface irrigation using porous (PRP) and emitting (GRP) pipes at two installation depths (25 and 35 cm) on soil water distribution, potato germination, and yield under arid conditions in Saudi Arabia. Soil water content was monitored using volumetric sampling, EnviroSCAN sensors, and HYDRUS modeling, with strong agreement observed among methods (R² ≥ 0.92). Results showed that shallow emitter placement (25 cm) combined with intermittent irrigation (five pulses, WF5C) maximized soil water retention in the root zone, reducing deep percolation losses. The GRP_25cm treatment improved soil water content by up to 140.7% at 30 cm depth and achieved the highest germination (74–83%) and yields (164.5–171.7 kg). In contrast, deeper installations (35 cm) consistently underperformed. Overall, intermittent irrigation enhanced water distribution and plant performance compared with continuous flow, leading to a 40–49% yield increase. These findings highlight the importance of emitter type, placement depth, and irrigation scheduling in optimizing water-use efficiency and plant productivity. The study provides practical recommendations for sustainable irrigation strategies in arid and hyper-arid regions facing increasing water scarcity. Full article

This research examines the otolith microchemical characteristics of the critically endangered kunming snout trout (Schizothorax grahami) collected from the sources section endemic to the Chishui River, China, a tributary of the upper Yangtze River, and the metal concentrations in the water of fish habitats. Among the analyzed elements, strontium (Sr) exhibited consistent distribution patterns across otolith rings, as observed through face-scan imagery (scanning the polished surface of the otolith cut), with a relatively low coefficient of variation. Statistical analysis using a paired two-tailed t-test revealed significant differences in Sr:Ca ratios among samples from the three river sections. Notably, magnesium (Mg) levels in the otolith core during the early life stages of the fish were notably higher compared to non-core regions. Similarly, Mg concentrations of water were elevated in the spawning grounds relative to non-spawning areas. This suggests that otolith Mg content may be influenced by the specific water conditions of the spawning grounds. Furthermore, Mg:Ca ratios in the otolith core displayed significant variation among samples from U3, L2, and other sites, implying that the fish in these samples originated from distinct spawning locations. These findings demonstrate that strontium and magnesium in otoliths can serve as effective markers for reconstructing the life history of S. grahami in the Chishui River and can contribute to the management of different fish stocks. Full article

Nosemosis is a disease caused by microsporidia, which are strictly intracellular pathogens, currently considered to be most closely related to fungi. These microscopic parasites infect a variety of hosts, significantly affecting honeybees (Apis mellifera). Nosemosis is one of the most serious diseases of bees and is caused primarily by two species: Nosema apis and Nosema ceranae. This infection adversely affects the digestive tract of the bees, causes a reduction in their vitality, and can lead to the death of entire colonies. The diagnosis of nosemosis has undergone extensive development. Traditionally, the identification of microsporidia was performed by examination of bee digestive tract (macerated) by light microscopy. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) are expensive methods that require skilled personnel and were used only when high resolution was necessary. Modern methods, such as polymerase chain reaction (PCR), allow detection of infection at species and genotype levels, thereby increasing the accuracy of diagnosis. Despite advances in molecular techniques, research into nosemosis still faces challenges. This review focuses on a comparison of different diagnostic techniques and their pitfalls that can be integrated into strategies to combat nosemosis and protect the health of honeybee colonies. Full article

Tunnels, as symmetric structures, are critical components of transportation infrastructure, particularly in mountainous regions. However, tunnel linings are prone to spalling after long-term service, posing significant safety risks. Although 3D laser scanning enables remote measurement of tunnel linings, existing surface fitting methods face challenges such as insufficient accuracy and high computational cost in quantifying spalling parameters. To address these issues, this study leverages the symmetrical geometry of tunnels to propose a curvature variance-based threshold segmentation method using limited point cloud data. First, the tunnel center axis is accurately determined via Sequential Quadratic Programming and the Quasi-Newton method. Noise and outliers are then removed based on geometric properties. Triangular meshes are constructed, and curvature variance is used as a threshold to extract spalling regions. Finally, surface reconstruction is applied to quantify spalling extent. Experiments in both laboratory and fire-damaged tunnel environments demonstrate that the method accurately extracts and quantifies lining spalling, with an average error of approximately 9.70%. This study underscores the potential of the proposed approach for broad application in tunnel inspection, as it will provide a basis for assessing the structural safety of tunnel linings. Full article

Diabetic pregnancy increases the offspring’s risk of neonatal and adult cardiovascular disease (CVD). We previously used a rat model (Sprague–Dawley) to show that diabetic pregnancy impairs mitochondrial bioenergetics, dynamics, mitophagy, and quality control in the offspring’s heart, and we hypothesized that mitochondrial dysfunction during early development influences the adult myocardium structure to confer cardiometabolic disease risk with aging. Here, we used 3D serial block face-scanning electron microscopy (SBF-SEM) to analyze perinuclear (PN) and intrafibrillar (IF) mitochondrial networks in the left ventricular sections from control and pregestational diabetes-exposed newborn (NB) rats that were three-week-old and four-month-old. Diabetes-exposed myocardium had 50% fewer PN and 20% fewer IF mitochondria at birth but counts increased more rapidly, resulting in no difference at three weeks and 35% more PN and 49% more IF mitochondria by four months. Despite rising counts, mitochondria volumes remained significantly lower at every developmental timepoint. This shows that diabetic pregnancy causes maldevelopment of the myocardial mitochondrial reticulum which likely contributes to adult CVD. Full article

Background/Objectives: Pharmaceutical cocrystallization offers a promising strategy to enhance drug properties while preserving molecular integrity. Ezetimibe, a BCS Class II hypolipidemic agent, faces therapeutic limitations due to poor aqueous solubility. This study aimed to systematically evaluate cocrystallization of ezetimibe with organic acid (benzoic, tartaric, or succinic acid) at varying stoichiometric ratios (1:0.5–1:2) to optimize physicochemical properties and oral bioavailability. Methods: Cocrystals were prepared via solvent evaporation (SEV) and solvent/anti-solvent (SAS) methods. Structural characterization included Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), and powder/single-crystal X-ray diffraction (PXRD/SCXRD). Physicochemical performance was assessed through saturation solubility, in vitro dissolution, and in vivo pharmacokinetics in male Sprague Dawley rats (n = 4/group). Results: Benzoic acid cocrystals (1:2 ratio, SEV) showed O−H⋯N hydrogen bonding (FTIR band shifts: 2928 → 3264 cm⁻¹) and novel crystalline phases (12.4°, 16.7°, and 24.9°). SCXRD confirmed monoclinic P2₁/n symmetry (a = 5.42 Å, b = 5.05 Å) for benzoic acid cocrystals. Ezetimibe/benzoic acid cocrystals (1:2) achieved 64-fold solubility enhancement and 2× faster dissolution vs. pure ezetimibe. Pharmacokinetics revealed 3× higher Cmax (18.38 ng/mL) and 4× greater AUC (40.36 h·ng/mL) for optimized cocrystals. Tartaric and succinic acid cocrystals showed moderate improvements, with melting points intermediate between parent compounds. Conclusions: Both stoichiometry and preparation method strongly determined cocrystal performance. Benzoic acid at a 1:2 ratio via SEV demonstrated superior solubility, dissolution, and bioavailability, addressing ezetimibe’s formulation challenges. These findings underscore the potential of rational cocrystal design to overcome solubility barriers in oral dosage development, particularly for hydrophobic therapeutics. Full article

Additive manufacturing via stereolithography (SLA) enables the fabrication of highly customized lattice structures, yet the interplay between geometry and graded density in defining mechanical behavior remains underexplored. This research investigates the mechanical behavior and failure mechanisms of cylindrical lattice structures considering uniform, linear, and quadratic density variations. Various configurations, including IsoTruss, face-centered cubic (FCC)-type cells, Kelvin structures, and Tet oct vertex centroid, were examined under a complete factorial design that allowed a thorough exploration of the interactions between lattice geometry and density variation. A 3D printer working with SLA was used to fabricate the models. For the analysis, a universal testing machine, following ASTM D638-22 Type I and ASTM D1621-16 standards, was used for tension and compression tests. For microstructural analysis and surface inspection, a scanning electron microscope and a digital microscope were used, respectively. Results indicate that the IsoTruss configuration with linear density excelled remarkably, achieving an impressive energy absorption of approximately 15 MJ/m³ before a 44% strain, in addition to presenting the most outstanding mechanical properties, with a modulus of elasticity of 613.97 MPa, a yield stress of 22.646 MPa, and a maximum stress of 49.193 MPa. On the other hand, the FCC configuration exhibited the lowest properties, indicating lower stiffness and mechanical strength in compression, with an average modulus of elasticity of 156.42 MPa, a yield stress of 5.991 MPa, and the lowest maximum stress of 14.476 MPa. The failure modes, which vary significantly among configurations, demonstrate the substantial influence of the lattice structure and density distribution on structural integrity, ranging from localized bending in IsoTruss to spalling in FCC and shear patterns in Kelvin. This study emphasizes the importance of selecting fabrication parameters and structural design accurately. This not only optimizes the mechanical properties of additively manufactured parts but also provides essential insights for the development of new advanced materials. Overall, the study demonstrates that both lattice geometry and density distribution play a crucial role in determining the structural integrity of additively manufactured materials. Full article

In the booming digital economy, data circulation—particularly for massive multimodal data generated by IoT sensor networks—faces critical challenges: ambiguous ownership and broken cross-domain traceability. Traditional property rights theory, ill-suited to data’s non-rivalrous nature, leads to ownership fuzziness after multi-source fusion and traceability gaps in cross-organizational flows, hindering marketization. This study aims to establish native ownership confirmation capabilities in trusted IoT-driven data ecosystems. The approach involves a dual-factor system: the collaborative extraction of text (from sensor-generated inspection reports), numerical (from industrial sensor measurements), visual (from 3D scanning sensors), and spatio-temporal features (from GPS and IoT device logs) generates unique SHA-256 fingerprints (first factor), while RSA/ECDSA private key signatures (linked to sensor node identities) bind ownership (second factor). An intermediate state integrates these with metadata, supported by blockchain (consortium chain + IPFS) and cross-domain protocols optimized for IoT environments to ensure full-link traceability. This scheme, tailored to the characteristics of IoT sensor networks, breaks traditional ownership confirmation bottlenecks in multi-source fusion, demonstrating strong performance in ownership recognition, anti-tampering robustness, cross-domain traceability and encryption performance. It offers technical and theoretical support for standardized data components and the marketization of data elements within IoT ecosystems. Full article

Investigating the pore structure and understanding the relationship between pore characteristics and mechanical properties are crucial to research in the study of cement mortar. At present, the segmentation of large-scale concrete pores is mainly conducted using traditional algorithms or software, which are time-consuming and operate in a semi-automated manner. However, the application of these methods faces challenges when analyzing large-scale rock pores due to factors such as a lack of data, artifacts, and inconsistent contrast. In this study, six series of cement mortars were subjected to real-time CT scanning under uniaxial loading (RT-CT) to collect real-time three-dimensional data on the evolution of pore structures during loading. To address issues such as artifacts and inconsistent contrast, a new augmentation method was proposed to overcome artifacts and enhance contrast consistency. Finally, the augmented dataset was utilized for training, and the Fast R-CNN algorithm served as the framework for developing the pore recognition model. The results indicate that the improved algorithm demonstrates enhanced convergence and greater accuracy in pore segmentation. A mathematical model is developed to relate uniaxial compressive strength (UCS) to pore fractal dimension and porosity, based on pore segmentation analysis. The fractal dimensions evolution of each specimen is consistent with the progressive failure indicated by the strain-stress curve. Under uniaxial loading, specimens with a 4:1 cement–sand ratio exhibited peak strength. The incorporation of fractals improved particle contact, thereby facilitating the formation of the skeletal structure. These efforts contribute to improving the identification of the deformation of cement mortars. Full article