Search Results (2,828)

The single-crystal diamond (SCD) possessing both favorable dielectric properties and low stress is esteemed as the ideal material for terahertz windows. The intrinsic step-like growth pattern of SCD can easily lead to stress concentration and a decrease in dielectric performance. In this study, a “two-step method” was designed to optimize the growth mode of SCD. A novel large platform growth pattern has been achieved by controlling diamond seed crystal etching and the epitaxial layer growth process. The experimental results indicate that, compared with the traditional step-like growth model, the root mean square (RMS) roughness of as-prepared SCD reduced from 5 nanometers (step growth) to 0.4~1.0 nanometers (platform growth) within a 5 μm × 5 μm area. Furthermore, the growth step height difference diminished from 30 nm to 3~4 nm, thereby mitigating stress induced by steps to a mere 0.1976 GPa. Additionally, at frequencies ranging from 0.1 to 3 THz, the diamond windows exhibit lower refractive index, dielectric constant, and dielectric loss. Finally, large platform growth effectively reduces phenomena such as dislocation pile-up brought about by step growth, achieving low-damage ultra-precision machining of diamond windows measuring 1 mm in diameter. Full article

Acoustic scattering is a highly effective tool for non-destructive control and structural analysis. In many real-world applications, understanding acoustic scattering is essential for accurately detecting and characterizing defects, assessing material properties, and evaluating structural integrity without causing damage. One of the most critical aspects of characterizing targets—such as plates, cylinders, and tubes immersed in water—is the analysis of the phase and group velocities of antisymmetric circumferential waves (A₁). Phase velocity helps identify and characterize wave modes, while group velocity allows for tracking energy, detecting, and locating anomalies. Together, they are essential for monitoring and diagnosing cylindrical shells. This research employs a Sugeno fuzzy inference system (SFIS) combined with a Fuzzy Subtractive Clustering (FSC) identification technique to predict the velocities of antisymmetric (A₁) circumferential signals propagating around an infinitely long cylindrical shell of different b/a radius ratios, where a is the outer radius, and b is the inner radius. These circumferential waves are generated when the shell is excited perpendicularly to its axis by a plane wave. Phase and group velocities are determined by using resonance eigenmode theory, and these results are used as training and testing data for the fuzzy model. The proposed approach demonstrates high accuracy in modeling and predicting the behavior of these circumferential waves. The fuzzy model’s predictions show excellent agreement with the theoretical results, as confirmed by multiple error metrics, including the Mean Absolute Error (MAE), Standard Error (SE), and Mean Relative Error (MRE). Full article

Carbon fiber-reinforced polymer (CFRP) composites have excellent mechanical properties, but their performance is hampered by delamination caused by weak interfacial bonding and resin-rich region (RRR). This research has proposed an interleaving film to improve interlaminar structure and mechanical properties by adding polyacrylonitrile (PAN) fiber into the epoxy interlayer of the CFRP laminates. The PAN fiber/epoxy resin (PANER) interleaving film could be prepared, which was beneficial to hinder crack initiation paths and improve the load transfer. Flexural and compression performance testing results showed optimum performance was obtained when 2 wt.% PAN fiber was added, and an increment of 28.6% was obtained in the flexural strength and 11.7% increment in compressive strength. The damaged energy absorption was improved up to 21.4% and 11.3% for the flexural and compressive properties, respectively. The overall thickness increments in the interlayer with PANER interleaving film were approximately 4–9 μm. X-Ray micro-computed tomography and scanning electron microscopy observations exhibited the potential of PAN fiber in the reduction of RRR, resulting in modes replacement from delamination-dominant failure to crossing-multi-layer failure. In all, PANER interleaving film at the interlayer has been confirmed to be an effective approach to produce a simple reinforcement technology for FRP laminates. Full article

Macro-scale modeling is a fundamental approach for assessing structural damage and occupant comfort in urban high-rises during earthquakes or typhoons. The key to its effectiveness is accurately reproducing dynamic responses and extracting modal characteristics. The critical issue is whether the macro-scale model can effectively capture Flexure-Shear Coupled (FSC) dynamic behavior. This paper proposes a macro-scale modeling method for high-rise structures with FSC dynamic behavior using deep learning (DL). FSC dynamic behavior is quantified by establishing Displacement Interaction Coefficients (DInC) under each mode shape. To account for the flexural resistance of horizontal members and the anti-overturning contribution of vertical members in high-rise structures, equivalent stiffness parameters representing horizontal and vertical members are introduced into the Lumped Parameter Model (LPM), enhancing the flexibility of the macro-scale model in expressing FSC dynamic behavior. The DInCs are used as input features to identify the LPM’s stiffness parameters, enabling efficient macro-scale modeling. The method was validated on a frame and a frame-core tube structure by comparing dynamic characteristics with their detailed finite element models. This method holds engineering application potential in areas requiring highly accurate and rapid structural characteristic or response calculations, such as seismic response analysis and design optimization of high-rise structures. Full article

This study systematically investigates the influence of laser pulse duration on cutting efficiency, heat-affected-zone (HAZ) formation, and mechanical integrity during carbon fiber-reinforced polymer (CFRP) laser cutting. Three distinct pulse-width lasers—picosecond, nanosecond, and quasi-continuous-wave (QCW)—are compared. Results show that pulse duration governs material removal mechanisms and HAZ extent: the nanosecond laser achieves the smallest HAZ and minimal porosity; the picosecond laser exhibits limited thermal accumulation due to low average power; and the QCW laser induces the largest HAZ (11.6 times that of the nanosecond laser) and significant porosity. Cutting efficiency scales inversely with pulse width, with single-hole processing times of 480.4 s for picosecond-laser cutting, 76.8 s for nanosecond-laser cutting, and 4.028 s for QCW-laser cutting, reflecting a transition from thermal ablation to mechanical spallation. Mechanical testing reveals that while tensile and flexural strengths vary by less than 5% across laser types, damage morphology and failure modes differ significantly. In situ digital image correlation (DIC) and 3D CT imaging show that longitudinal plies fail via fiber pull-out, whereas transverse plies fail via interfacial debonding. QCW-laser-cut specimens exhibit more uniform strain distribution and higher damage tolerance. An optimized process parameter is proposed: nanosecond-laser cutting at 200 W and 20 kHz achieves a HAZ of less than 50 µm and a cutting time of less than 80 s, offering the best balance between efficiency and quality. Full article

Natural rock materials, containing micro-cracks and pore defects, significantly alter their mechanical behavior. This study investigated fracture interactions of red sandstone containing double close-round holes (diameter: 10 mm; bridge angle: 30°, 45°, 60°, 90°) using acoustic emission (AE) monitoring and the discrete element simulations method (DEM), which was a novel methodology for revealing dynamic failure mechanisms. The uniaxial compression tests showed that hole geometry critically controlled failure modes: specimens with 0° bridge exhibited elastic–brittle failure with intense AE energy releases and large fractures, while 45° arrangements displayed elastic–plastic behaviors with stable AE signal responses until collapse. The quantitative AE analysis revealed that the fracture-type coefficient k had a distinct temporal clustering characteristic, demonstrating the spatiotemporal synchronization of tensile and shear crack initiation and propagation. Furthermore, numerical simulations identified a critical stress redistribution phenomenon, that axial compressive force chains concentrated along the loading axis, forming continuous longitudinal compression zones, while radial tensile dispersion dominated hole peripheries. Crucially, specimens with 45° and 90° bridges induced prominently symmetric tensile fractures (85° to horizontal direction) and shear-dominated failure near junctions. These findings can advance damage prediction in discontinuous geological media and offer direct insights for optimizing excavation sequences and support design in cavern engineering. Full article

The synergistic preparation of geopolymer from lithium slag, fly ash, and slag for underground construction can facilitate the extensive recycling of lithium slag. The effects of different activator moduli and water–binder ratios on the mechanical properties and damage mechanisms of the lithium-slag-based geopolymer were investigated by uniaxial compression tests and acoustic emission (AE) monitoring. The results show that, based on a comprehensive evaluation of peak stress, crack closure stress, plastic deformation stress, and elastic modulus, the optimal activator modulus is determined to be 1.0, and the optimal water-to-binder ratio is 0.42. At low modulus values (0.8 and 1.0) and low water–binder ratio (0.42), the AE events exhibit a steady pattern, indicating slow crack initiation and propagation within the geopolymer; with the increasing activator modulus and water-to-binder ratios, the frequency of AE events increases significantly, indicating more-frequent crack propagation and stress mutation within the geopolymer. Similarly, when the modulus is 0.8 or 1.0 and the water–binder ratio is 0.42, the sample presents a macroscopic tensile failure mode; as the modulus and water–binder ratio increase, the sample presents a tensile–shear composite failure mode. The energy evolution laws of geopolymer specimens with different activator moduli and water-to-binder ratios were analyzed, and a damage constitutive model was established. The results indicate that, with optimized mix proportions, the material can be used as a supporting material for underground spaces. Full article

Clarifying the differential effects of temperature gradient and temperature change rate on the evolution of rock fractures and damage mechanism under thermal shock is of great significance for the development and utilization of deep geothermal resources. In this study, granite samples at different temperatures (20 °C, 150 °C, 300 °C, 450 °C, 600 °C, and 750 °C) were subjected to rapid cooling treatment with liquid nitrogen. After the thermal treatment, a series of tests were conducted on the granite, including wave velocity test, uniaxial compression experiment, computed tomography scanning, and scanning electron microscopy test, to explore the influence of thermal shock on the physical and mechanical parameters as well as the meso-structural damage of granite. The results show that with the increase in heat treatment temperature, the P-wave velocity, compressive strength, and elastic modulus of granite gradually decrease, while the peak strain gradually increases. Additionally, the failure mode of granite gradually transitions from brittle failure to ductile failure. Through CT scanning experiments, the spatial distribution characteristics of the pore–fracture structure of granite under the influence of different temperature gradients and temperature change rates were obtained, which can directly reflect the damage degree of the rock structure. When the heat treatment temperature is 450 °C or lower, the number of thermally induced cracks in the scanned sections of granite is relatively small, and the connectivity of the cracks is poor. When the temperature exceeds 450 °C, the micro-cracks inside the granite develop and expand rapidly, and there is a gradual tendency to form a fracture network, resulting in a more significant effect of fracture initiation and permeability enhancement of the rock. The research results are of great significance for the development and utilization of hot dry rock and the evaluation of thermal reservoir connectivity and can provide useful references for rock engineering involving high-temperature thermal fracturing. Full article

As an important technology to enhance nutrient use efficiency and reduce agricultural non-point source pollution, controlled-release fertilizers (CRFs) have been widely applied in modern agriculture. However, during packaging, transportation, and field application, CRF particles are prone to mechanical impacts, which can lead to particle fragmentation and damage to the controlled-release coating. This compromises the release kinetics, increases nutrient loss risk, and ultimately exacerbates environmental issues such as eutrophication. Currently, studies on the impact-induced fragmentation behavior of CRF particles remain limited, and there is an urgent need to investigate their fragmentation susceptibility mechanisms from the perspective of internal stress evolution. In this study, the mechanical properties of CRF particles were first experimentally determined to obtain essential parameters. A two-layer finite element model representing the coating and core structure of the particles was then constructed, and a fragmentation susceptibility index was proposed as the key evaluation criterion. The index, defined as the ratio of fractured volume to peak impact energy, reflects the efficiency of energy conversion at the critical moment of particle rupture (1–5). An explicit dynamic simulation framework incorporating multiple influencing factors—equivalent diameter, sphericity, impact material, velocity, and angle—was developed to analyze fragmentation behavior from the perspective of energy transformation. Based on the observed effects of these variables on fragmentation susceptibility, three regression models were developed using response surface methodology to quantitatively predict fragmentation susceptibility. Comparative analysis between the simulation and experimental results showed a fragmentation rate error range of 0–11.47%. The findings reveal the relationships between particle fragmentation modes and energy responses under various impact conditions. This research provides theoretical insights and technical guidance for optimizing the mechanical stability of CRFs and developing environmentally friendly fertilization strategies. Full article

Larch shoot blight, caused by Neofusicoccum laricinum, threatens global larch resources, while conventional chemical control is constrained by pollution and resistance. To address this gap, we integrated metabolomics, transcriptomics, and antifungal efficacy assays to identify Fraxetin, a disease-induced phytoalexin, and to elucidate its antifungal activity and mechanism. Metabolomics showed infection-triggered accumulation of Fraxetin in resistant Larix olgensis shoots. Antifungal experiments showed that within the range of 68–1088 μg/mL, the optimal antifungal concentration was 1088 μg/mL. When inoculated larches were treated with 1088 μg/mL Fraxetin, the maximum inhibition rate of pathogen growth reached 66.67% within 12 days, and the symptoms of the treated plants were alleviated. Transcriptomics revealed activation of damage responses, disruption of oxidative homeostasis, and compromised membrane integrity in the pathogen under Fraxetin treatment. Physiological measurements confirmed increased lipid peroxidation, redox collapse, membrane leakage, and reduced fungal viability. These findings indicate a lipid peroxidation–mediated oxidative–membrane mode of action and support the potential of plant-derived Fraxetin for more sustainable management of larch shoot blight. Full article

Chicken meat is highly consumed worldwide due to its nutritional value, but its high water content and abundance of polyunsaturated fatty acids make it particularly vulnerable to structural and oxidative damage during freezing and thawing. Slow freezing, in particular, generates large ice crystals that severely impair water-holding capacity (WHC), increase drip loss, promote color deterioration, and intensify protein and lipid oxidation. Innovative thawing strategies are therefore required to mitigate these quality losses. Ultrasound (US) has been successfully applied to accelerate thawing of fast-frozen meat; however, its potential for slowly frozen chicken breast remains poorly understood. This study aimed to evaluate the effects of US-assisted thawing at two frequencies (25 and 130 kHz), two amplitudes (100% and 60%), and three operating modes (normal, sweep, and degas) on the quality of slowly frozen chicken breast. Conventional thawing required 50 min, yielding WHC of 9.87%, drip loss of 4.65%, free sulfhydryls of 16.38 µmol/g, and ∆E of 3.91. In contrast, the optimized US condition (25 kHz, 100% amplitude, sweep mode) thawed samples in only 18 min, with markedly improved WHC (23.14%), reduced drip loss (3.25%), higher preservation of free sulfhydryls (24.69 µmol/g), and minimal color change (∆E = 3.72). Conversely, less effective parameters (e.g., 130 kHz, 60% amplitude, normal mode) prolonged thawing and compromised quality, with WHC dropping to 9.96% and drip loss increasing to 9.05%. Overall, US reduced thawing time under all conditions, but quality responses depended strongly on the applied parameters. The present findings demonstrate the novelty of optimizing US frequency, amplitude, and mode for thawing slowly frozen chicken breast, highlighting sweep mode at 25 kHz and 100% amplitude as the most effective strategy. Future research should explore its scalability and industrial applicability for poultry processing. Full article

The aim of this pilot in vitro study is to investigate the fracture strength of hybrid abutment crowns (HACs) made of a 3D-printable, tooth-colored, ceramic-reinforced composite (CRC). Based on an upper first premolar, a crown was designed, and specimens were additively fabricated from a composite material (VarseoSmile Crown plus) (N = 32). The crowns were bonded to standard abutments using a universal resin cement. Half (n = 16) of the samples were subjected to artificial aging, during which three samples suffered minor damage. All specimens were mechanically loaded at an angle of 30° to the implant axis. In addition, an FEM simulation was computed. Statistical analysis was performed at a significance level of p < 0.05. The mean fracture load without aging was 389.04 N (SD: 101.60 N). Two HACs suffered screw fracture, while the crowns itself failed in all other specimens. In the aged specimens, the mean fracture load was 391.19 N (SD: 143.30 N). The failure mode was predominantly catastrophic crown fracture. FEM analysis showed a maximum compressive stress of 39.79 MPa, a maximum tensile stress of 173.37 MPa and a shear stress of 60.29 MPa when loaded with 389 N. Within the limitations of this pilot study, the tested 3D-printed hybrid abutment crowns demonstrated fracture resistance above a clinically acceptable threshold, suggesting promising potential for clinical application. However, further investigations with larger sample sizes, control groups, and clinical follow-up are required. Full article

This study investigates the uniaxial compression failure of magnesium-based wood-like material (MWM) prisms (100 × 100 × 300 mm³) using digital image correlation (DIC). The results revealed an average compressive strength of 8.76 MPa and a dominant failure mode with Y-shaped or inclined penetrating cracks. A novel piecewise constitutive model was established, combining a quartic polynomial and a rational fraction, demonstrating high fitting accuracy. Critically, the proportional limit was identified to be very low (20–35% of peak stress), attributed to early-stage damage from fiber–matrix interfacial defects. DIC analysis quantitatively distinguished dual crack initiation modes, pure mode I (occurring at ≈100% peak load) and mixed mode I/II (initiating earlier at 90.02% peak load), demonstrating that tensile shear coupling accelerates failure. These findings provide critical mechanistic insights and a reliable model for optimizing MWM in sustainable construction. Future work will explore the material’s behavior under multiaxial loading. Full article

Electrochemical CO₂ reduction reaction (CO₂RR) is a key technology for achieving carbon neutrality and efficient utilization of renewable energy, capable of converting CO₂ into high-value-added carbon-based fuels and chemicals. Copper (Cu)-based catalysts have attracted significant attention due to their unique performance in generating multi-carbon (C₂₊) products such as ethylene and ethanol; however, there are still many controversies regarding their complex reaction mechanisms, active sites, and the dynamic evolution of intermediates. In situ Raman spectroscopy, with its high surface sensitivity, applicability in aqueous environments, and precise detection of molecular vibration modes, has become a powerful tool for studying the structural evolution of Cu catalysts and key reaction intermediates during CO₂RR. This article reviews the principles of electrochemical in situ Raman spectroscopy and its latest developments in the study of CO₂RR on Cu-based catalysts, focusing on its applications in monitoring the dynamic structural changes of the catalyst surface (such as Cu⁺, Cu⁰, and Cu²⁺ oxide species) and identifying key reaction intermediates (such as *CO, *OCCO(*O=C-C=O), *COOH, etc.). Numerous studies have shown that Cu-based oxide precursors undergo rapid reduction and surface reconstruction under CO₂RR conditions, resulting in metallic Cu nanoclusters with unique crystal facets and particle size distributions. These oxide-derived active sites are considered crucial for achieving high selectivity toward C₂₊ products. Time-resolved Raman spectroscopy and surface-enhanced Raman scattering (SERS) techniques have further revealed the dynamic characteristics of local pH changes at the electrode/electrolyte interface and the adsorption behavior of intermediates, providing molecular-level insights into the mechanisms of selectivity control in CO₂RR. However, technical challenges such as weak signal intensity, laser-induced damage, and background fluorescence interference, and opportunities such as coupling high-precision confocal Raman technology with in situ X-ray absorption spectroscopy or synchrotron radiation Fourier transform infrared spectroscopy in researching the mechanisms of CO₂RR are also put forward. Full article

Arthritis and arthrosis are prevalent joint diseases that cause pain and disability, and their early diagnosis is crucial for preventing irreversible damage. Conventional diagnostic methods such as X-ray, ultrasound, and MRI have limitations in early detection, prompting interest in alternative techniques. This work presents the design and clinical evaluation of a prototype device for non-invasive early diagnosis of arthritis (inflammatory joint disease) and arthrosis (osteoarthritis) using infrared thermography and deep neural networks. The portable prototype integrates a Raspberry Pi 4 microcomputer, an infrared thermal camera, and a touchscreen interface, all housed in a 3D-printed PLA enclosure. A custom Flask-based application enables two operational modes: (1) thermal image acquisition for training data collection, and (2) automated diagnosis using a pre-trained ResNet50 deep learning model. A clinical study was conducted at a university clinic in a temperature-controlled environment with 100 subjects (70% with arthritic conditions and 30% healthy). Thermal images of both hands (four images per hand) were captured for each participant, and all patients provided informed consent. The ResNet50 model was trained to classify three classes (healthy, arthritis, and arthrosis) from these images. Results show that the system can effectively distinguish healthy individuals from those with joint pathologies, achieving an overall test accuracy of approximately 64%. The model identified healthy hands with high confidence (100% sensitivity for the healthy class), but it struggled to differentiate between arthritis and arthrosis, often misclassifying one as the other. The prototype’s multiclass ROC (Receiver Operating Characteristic) analysis further showed excellent discrimination between healthy vs. diseased groups (AUC, Area Under the Curve ~1.00), but lower performance between arthrosis and arthritis classes (AUC ~0.60–0.68). Despite these challenges, the device demonstrates the feasibility of AI-assisted thermographic screening: it is completely non-invasive, radiation-free, and low-cost, providing results in real-time. In the discussion, we compare this thermography-based approach with conventional diagnostic modalities and highlight its advantages, such as early detection of physiological changes, portability, and patient comfort. While not intended to replace established methods, this technology can serve as an early warning and triage tool in clinical settings. In conclusion, the proposed prototype represents an innovative application of infrared thermography and deep learning for joint disease screening. With further improvements in classification accuracy and broader validation, such systems could significantly augment current clinical practice by enabling rapid and non-invasive early diagnosis of arthritis and arthrosis. Full article