Search Results (424)

Magnetic nanoparticles (MNPs), especially iron oxide (Fe₃O₄), display distinctive superparamagnetic characteristics and elevated surface-area-to-volume ratios, facilitating improved physicochemical interactions with solutes and pollutants. These characteristics make MNPs strong contenders for use in water treatment applications. This research investigates the application of iron oxide MNPs synthesized via co-precipitation as innovative draw solutes in forward osmosis (FO) for treating synthetic produced water (SPW). The FO membrane underwent surface modification with sulfobetaine methacrylate (SBMA), a zwitterionic polymer, to increase hydrophilicity, minimize fouling, and elevate water flux. The SBMA functional groups aid in electrostatic repulsion of organic and inorganic contaminants, simultaneously encouraging robust hydration layers that improve water permeability. This adjustment is vital for sustaining consistent flux performance while functioning with MNP-based draw solutions. Material analysis through thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and Fourier-transform infrared spectroscopy (FTIR) verified the MNPs’ thermal stability, consistent morphology, and modified surface chemistry. The FO experiments showed a distinct relationship between MNP concentration and osmotic efficiency. At an MNP dosage of 10 g/L, the peak real-time flux was observed at around 3.5–4.0 L/m²·h. After magnetic regeneration, 7.8 g of retrieved MNPs generated a steady flow of ~2.8 L/m²·h, whereas a subsequent regeneration (4.06 g) resulted in ~1.5 L/m²·h, demonstrating partial preservation of osmotic driving capability. Post-FO draw solutions, after filtration, exhibited total dissolved solids (TDS) measurements that varied from 2.5 mg/L (0 g/L MNP) to 227.1 mg/L (10 g/L MNP), further validating the effective dispersion and solute contribution of MNPs. The TDS of regenerated MNP solutions stayed similar to that of their fresh versions, indicating minimal loss of solute activity during the recycling process. The combined synergistic application of SBMA-modified FO membranes and regenerable MNP draw solutes showcases an effective and sustainable method for treating produced water, providing excellent water recovery, consistent operational stability, and opportunities for cyclic reuse. Full article

In this study, dry sliding wear tests were carried out on Er, Zr-microalloyed Al-Zn-Mg alloys with different Zn/Mg ratios under 30–70 N loads. The effects of the Zn/Mg content ratio and Er microalloying on the friction coefficient, wear volume loss, worn surface, and wear debris during the friction process of Al-Zn-Mg alloys were analyzed. At the load of 30 N, abrasive wear, fatigue wear, and adhesive wear were synergistically involved. At a load of 50 N, the abrasive wear dominated, accompanied by fatigue wear and adhesive wear. At a load of 70 N, the primary wear mechanisms transitioned to abrasive wear and fatigue wear, with additional adhesive wear and oxidative wear observed. Reducing the Zn/Mg ratio mitigated wear volume across all tested loads. For the Al4.5Zn1.5Mg alloy, Er microalloying significantly reduced wear volume under moderate-to-low loads (30 N, 50 N). Full article

Lost circulation is a major challenge in oil and gas drilling operations, severely restricting drilling efficiency and compromising operational safety. Conventional bridging and plugging materials rely on precise particle-to-fracture size matching, resulting in low success rates. Self-healing gels penetrate loss zones as discrete particles that progressively swell, accumulate, and self-repair in integrated gel masses to effectively seal fracture networks. Self-healing gels effectively overcome the shortcomings of traditional bridging agents including poor adaptability to fractures, uncontrollable gel formation of conventional downhole crosslinking gels, and the low strength of conventional pre-crosslinked gels. This work employs stearyl methacrylate (SMA) as a hydrophobic monomer, acrylamide (AM) and acrylic acid (AA) as hydrophilic monomers, and graphene oxide (GO) as an inorganic dopant to develop a GO-based self-healing organic–inorganic hybrid plugging material (SG gel). The results demonstrate that the incorporation of GO significantly enhances the material’s mechanical and rheological properties, with the SG-1.5 gel exhibiting a rheological strength of 3750 Pa and a tensile fracture stress of 27.1 kPa. GO enhances the crosslinking density of the gel network through physical crosslinking interactions, thereby improving thermal stability and reducing the swelling ratio of the gel. Under conditions of 120 °C and 6 MPa, SG-1.5 gel demonstrated a fluid loss volume of only 34.6 mL in 60–80-mesh sand bed tests. This gel achieves self-healing within fractures through dynamic hydrophobic associations and GO-enabled physical crosslinking interactions, forming a compact plugging layer. It provides an efficient solution for lost circulation control in drilling fluids. Full article

Objectives: Observational studies have shown that chronic obstructive pulmonary disease (COPD) is associated with an increased risk of hearing impairment. However, causality remains unclear, including with respect to lung function. This study aimed to investigate the associations of lung function and COPD with hearing impairment in the UK Biobank and confirm potential causalities using Mendelian randomization (MR). Methods: Cross-sectional analyses were performed using logistic regression models in a subsample of the UK Biobank. Two-sample MR analyses were performed on summary statistics for forced expiratory volume in one second (FEV1), forced vital capacity (FVC), COPD, and sensorineural hearing loss. Results: FEV1 and FVC were negatively associated with hearing impairment, with odds ratios (95% confidence intervals) of 0.80 (0.77, 0.84) and 0.80 (0.76, 0.83), respectively. COPD was positively associated with hearing impairment, with an odds ratio (95% confidence interval) of 1.10 (1.02, 1.18). In the MR analyses, a negative association was found between FVC and sensorineural hearing loss, with an odds ratio (95% confidence interval) of 0.91 (0.83, 0.99). For FVE1 and COPD, no significant associations were found. Conclusions: The results of this study showed that FVC was causally associated with hearing impairment, suggesting a potential protective effect of FVC on hearing impairment. Full article

In this study, we systematically investigated the characteristic parameter evolution laws of thermal runaway with respect to 18,650 lithium-ion batteries (LIBs) under thermal abuse conditions at five state-of-charge (SOC) levels: 0%, 25%, 50%, 75%, and 100%. In our experiments, we combined infrared thermography, mass loss analysis, temperature monitoring, and gas composition detection to reveal the mechanisms by which SOC affects the trigger time, critical temperature, maximum temperature, mass loss, and gas release characteristics of thermal runaway. The results showed that as the SOC increases, the critical and maximum temperatures of thermal runaway increase notably. At a 100% SOC, the highest temperature on the positive electrode side reached 1082.1 °C, and the mass loss increased from 6.90 g at 0% SOC to 25.75 g at 100% SOC, demonstrating a salient positive correlation. Gas analysis indicated that under high-SOC conditions (75% and 100%), the proportion of flammable gases such as CO and CH₄ produced during thermal runaway significantly increases, with the CO/CO₂ ratio exceeding 1, indicating intensified incomplete combustion and a significant increase in fire risk. In addition, flammability limit analysis revealed that the lower explosive limit for gases is lower (17–21%) at a low SOC (0%) and a high SOC (100%), indicating greater explosion risks. We also found that the composition of gases released during thermal runaway varies substantially at different SOC levels, with CO, CO₂, and CH₄ accounting for over 90% of the total gas volume, while toxic gases, such as HF, although present in smaller proportions, pose noteworthy hazards. Unlike prior studies that relied on post hoc analysis, this work integrates real-time multi-parameter monitoring (temperature, gas composition, and mass loss) and quantitative explosion risk modeling (flammability limits via the L-C formula). This approach reveals the unique dynamic SOC-dependent mechanisms of thermal runaway initiation and gas hazards. This study provides theoretical support for the source tracing of thermal runaway fires and the development of preventive LIB safety technology and emphasizes the critical influence of the charge state on the thermal safety of batteries. Full article

To address the technical problems of broad droplet size spectrum, insufficient atomization uniformity, and spray drift in plant protection unmanned aerial vehicle (UAV) applications, this study developed a novel two-stage aerial electrostatic spraying device based on the coupled mechanisms of hydraulic atomization and electrostatic induction, and, through the integration of three-dimensional numerical simulation and additive manufacturing technology, a new two-stage inductive charging device was designed on the basis of the traditional hydrodynamic nozzle structure, and a synergistic optimization study of the charging effect and atomization characteristics was carried out systematically. With the help of a charge ratio detection system and Malvern laser particle sizer, spray pressure (0.25–0.35 MPa), charging voltage (0–16 kV), and spray height (100–1000 mm) were selected as the key parameters, and the interaction mechanism of each parameter on the droplet charge ratio (C/m) and the particle size distribution (Dv50) was analyzed through the Box–Behnken response surface experimental design. The experimental data showed that when the charge voltage was increased to 12 kV, the droplet charge-to-mass ratio reached a peak value of 1.62 mC/kg (p < 0.01), which was 83.6% higher than that of the base condition; the concentration of the particle size distribution of the charged droplets was significantly improved; charged droplets exhibited a 23.6% reduction in Dv50 (p < 0.05) within the 0–200 mm core atomization zone below the nozzle, with the coefficient of variation of volume median diameter decreasing from 28.4% to 16.7%. This study confirms that the two-stage induction structure can effectively break through the charge saturation threshold of traditional electrostatic spraying, which provides a theoretical basis and technical support for the optimal design of electrostatic spraying systems for plant protection UAVs. This technology holds broad application prospects in agricultural settings such as orchards and farmlands. It can significantly enhance the targeted deposition efficiency of pesticides, reducing drift losses and chemical usage, thereby enabling agricultural enterprises to achieve practical economic benefits, including reduced operational costs, improved pest control efficacy, and minimized environmental pollution, while generating environmental benefits. Full article

Conductive polymer composites (CPCs) are widely used in flexible electronics due to their tunable electrical properties and mechanical deformability. However, accurately predicting the evolution of conductive networks, particularly under compressive strain, remains a significant challenge. In this study, we developed a statistical mechanics model and an extended dynamic statistical mechanics model to quantitatively describe percolation behavior in CPCs. The static model incorporates filler geometry, aspect ratio (AR), and surface-to-volume ratio, and was validated using Monte Carlo simulations. Results show that the percolation threshold for spherical fillers was 0.11965, while significantly lower values of 0.00669 and 0.00203 were observed for plate- and rod-shaped fillers, respectively, confirming the enhanced connectivity of anisotropic particles. To capture strain-dependent behavior, a dynamic model was constructed using a Smoluchowski-type gain–loss framework. This model separates conductive network formation (gain) from network disconnection (loss) caused by filler alignment and Poisson-induced expansion. At high Poisson’s ratios (0.3 and 0.5), the model accurately predicted the reduction in connectivity, particularly for anisotropic fillers. Across all tested conditions, the model exhibited strong agreement with simulation data, with RMSE values ranging from 0.0004 to 0.0449. The results confirm that high AR fillers enhance conductivity under compression, while large Poisson’s ratios suppress network formation. These findings provide a reliable, physically grounded modeling framework for designing strain-sensitive devices such as flexible pressure sensors. Full article

Plain concrete specimens and FRP(Fiber Reinforced Polymer)-reinforced concrete specimens were fabricated to investigate concrete’s mechanical and surface degradation behaviors reinforced with carbon, basalt, glass, and aramid fiber-reinforced polymer under coupled sulfuric acid and freeze–thaw cycles. The compressive strength of fully wrapped FRP cylindrical specimens and the flexural load capacity of prismatic specimens with FRP reinforced to the pre-cracked surface, along with the dynamic elastic modulus and mass loss, were evaluated before and after acid–freeze cycles. The degradation mechanism of the specimens was elucidated through analysis of surface morphological changes captured in photographs, scanning electron microscopy (SEM) observations, and energy-dispersive spectroscopy (EDS) data. The experimental results revealed that after 50 cycles of coupled acid–freeze erosion, the plain cylindrical concrete specimens showed a mass gain of 0.01 kg. In contrast, after 100 cycles, a significant mass loss of 0.082 kg was recorded. The FRP-reinforced specimens initially demonstrated mass loss trends comparable to those of the plain concrete specimens. However, in the later stages, the FRP confinement effectively mitigated the surface spalling of the concrete, leading to a reversal in mass loss and subsequent mass gain. Notably, the GFRP(Glassfiber Reinforced Polymer)-reinforced specimens exhibited the most significant mass gain of 1.653%. During the initial 50 cycles of acid–freeze erosion, the prismatic and cylindrical specimens demonstrated comparable degradation patterns. However, in the subsequent stages, FRP reduced the exposed surface area-to-volume ratio of the specimens in contact with the acid solution, resulting in a marked improvement in their structural integrity. After 100 cycles of acid–freeze erosion, the compressive strength loss rate and flexural load capacity loss rate followed the ascending order: CFRP-reinforced < BFRP(Basalt Fiber Reinforced Polymer)-reinforced < AFRP(Aramid Fiber Reinforced Polymer)-reinforced < GFRP-reinforced < plain specimens. Conversely, the ductility ranking from highest to lowest was AFRP/GFRP > control group > BFRP/CFRP. A probabilistic analysis model was established to complement the experimental findings, encompassing the quantification of hazard levels and reliability indices. Full article

Background/Objectives: Hashimoto thyroiditis (HT) is an autoimmune disease affecting the thyroid, often leading to hypothyroidism, even in individuals with adequate iodine intake. Despite achieving biochemical euthyroidism through levothyroxine (LT4) therapy, many patients continue to experience persistent symptoms, likely due to ongoing thyroid autoimmunity. Photobiomodulation (PBM) has shown promise in treating autoimmune conditions, but its effect on thyroid volume (TV) remains unclear. This study aimed to assess the efficacy of PBM combined with supplements in restoring thyroid function and normalising TV compared to the use of supplements alone. Methods: Ninety-eight females aged 20–50 years old were divided into two groups: Group 1 received PBM and supplements and Group 2 received supplements only. The PBM parameters were as follows: 820 nm wavelength, 200 mW power, continuous mode, 20 s per point at 8 points (32 J/cm² per point), twice weekly for three weeks. Both groups received vitamin D3 supplementation (if serum < 40 ng/dL) and 100 µg of oral selenium daily. Results: Ninety-seven participants completed the study (51 in Group 1, 46 in Group 2). Group 1 showed significantly greater improvements in TV normalisation and weight loss and reductions in BMI, waist/hip circumference, waist-to-hip ratio, TSH, anti-TPO, anti-TG, and LT4 dosage (p < 0.05). Conclusions: This study demonstrates that low-fluence PBM combined with supplements can effectively improve thyroid function, reduce TV, and enhance anthropometric and clinical outcomes in HT patients. The protocol holds potential for broader application and further validation in larger trials. Full article

The protective materials for cultural relic buildings generally have a deficiency of relatively shallow penetration depth. Based on the principle of changing the permeability coefficient of cultural relic buildings by “water blocking water” and considering the characteristics of magnesium acrylate polymer and the requirement of extending the curing time, a method of modifying magnesium acrylate polymer with glycerol and sodium methyl silicate is proposed. Experimental studies on magnesium acrylate, glycerol–magnesium acrylate, and sodium methyl silicate—glycerol–magnesium acrylate polymers were carried out, and tests and analyses on curing time, swelling performance, water loss rate, and soil sample protection were conducted. The results show that the initiator concentration is a key factor affecting the curing rate of magnesium acrylate polymers. When the initiator content is ≥4%, the curing time is significantly shortened to 20–67 min, and the incorporation of glycerol prolongs the curing time by more than 100 min through the dilution reaction system. Glycerol modification significantly enhanced the swelling capacity of the polymer, with the swelling rate increasing by approximately 15–20% compared to the unmodified system. Sodium methyl silicate effectively improved the construction performance of magnesium acrylate and prevented the occurrence of bubbles. The optimal formula of magnesium acrylate polymer is 25% magnesium acrylate, 40% glycerol, and 2% sodium methyl silicate. While maintaining curing for 120 min, it features a high swelling rate (equilibrium swelling ratio Ew ≈ 0.32) and a low dehydration rate (dehydration rate ≤ 35% after 48 h), and has volume stability after interaction with soil samples. Full article

Metaconcrete (MC) is a class of engineered cementitious composites that integrates locally resonant inclusions to filter stress waves. While the dynamic benefits are well established, the effect of resonator content and geometry on static compressive resistance remains unclear. This study develops the first two-dimensional mesoscale finite-element model that explicitly represents steel cores, rubber coatings, and interfacial transition zones to predict the quasi-static behavior of MC. The model is validated against benchmark experiments, reproducing the 56% loss of compressive strength recorded for a 10.6% resonator volume fraction with an error of less than 1%. A parametric analysis covering resonator ratios from 1.5% to 31.8%, diameters from 16.8 mm to 37.4 mm, and coating thicknesses from 1.0 mm to 4.2 mm shows that (i) strength decays exponentially with volumetric content, approaching an asymptote at ≈20% of plain concrete strength; (ii) larger cores with thinner coatings minimize stiffness loss (<10%) while limiting strength reduction to 15–20%; and (iii) material properties of the resonator have a secondary influence (<6%). Two closed-form expressions for estimating MC strength and Young’s modulus (R² = 0.83 and 0.94, respectively) are proposed to assist with the preliminary design. The model and correlations lay the groundwork for optimizing MC that balances vibration mitigation with structural capacity. Full article

In this research work, two distinct types of three-dimensional (3D) capacitors were successfully fabricated, each with its own unique features and advantages. The first type of capacitor is centered around a 3D nanoporous structure. This structure is formed on a nickel substrate through anodic oxidation. After undergoing high-temperature thermal oxidation, a monolithic Ni-NiO-Pt metal–insulator–metal (MIM) capacitor with a nanoporous dielectric architecture is achieved. Structurally, this innovative design brings about several remarkable benefits. Due to the nanoporous structure, it has a significantly increased surface area, which can effectively store more charges. As a result, it exhibits an equivalent capacitance density of 69.95 nF/cm², which is approximately 18 times higher than that of its planar, non-porous counterpart. This high capacitance density enables it to store more electrical energy in a given volume, making it highly suitable for applications where miniaturization and high energy storage in a small space is crucial. The second type of capacitor makes use of Through-Glass Via (TGV) technology. This technology is employed to create an interdigitated blind-via array within a glass substrate, attaining an impressively high aspect ratio of 22.5:1 (with a via diameter of 20 μm and a depth of 450 μm). By integrating atomic layer deposition (ALD), a conformal interdigital electrode structure is realized. Glass, as a key material in this capacitor, has outstanding insulating properties. This characteristic endows the capacitor with a high breakdown field strength exceeding 8.2 MV/cm, corresponding to a withstand voltage of 5000 V. High breakdown field strength and withstand voltage mean that the capacitor can handle high-voltage applications without breaking down easily, which is essential for power-intensive systems like high-voltage power supplies and some high-power pulse-generating equipment. Moreover, due to the low-loss property of glass, the capacitor can achieve an energy conversion efficiency of up to 95%. Such a high energy conversion efficiency ensures that less energy is wasted during the charge–discharge process, which is highly beneficial for energy-saving applications and systems that require high-efficiency energy utilization. Full article

Autonomous inflow control devices (AICDs) offer a promising means of delaying early water breakthrough in heavy oil horizontal wells; yet, current design practices remain largely empirical. A three-dimensional, field-calibrated computational fluid dynamics (CFD) model was developed to establish a mechanistic basis that solves the transient Navier–Stokes equations for turbulent two-phase flow via a volume-of-fluid formulation. Pressure-controlled inflow boundaries were tuned to build up data from four Colombian heavy oil producers, enabling a quantitative comparison with production logs. Model predictions deviate by no more than ±14% for oil rate and ±10% for water rate over a 500-day horizon, providing confidence in subsequent scenario analysis. Replacing a slotted liner completion with optimally sized AICDs lowers cumulative water-cut by up to 93%, reduces annular friction losses by 18%, and cuts estimated life cycle CO₂ emissions per stock-tank barrel by 82%. Sensitivity analysis identifies nozzle diameter as the dominant design variable, with a nonlinear interaction between local drawdown pressure and the oil–water viscosity ratio. These findings demonstrate that CFD-guided AICD design can materially extend wells’ economic life while delivering substantial environmental benefits. The validated workflow establishes a low-risk, physics-based path for tailoring AICDs to reservoir conditions before field deployment. Full article

Background: Survival prediction in patients with brain metastases remains a major clinical challenge, where timely and individualized prognostic estimates are critical for guiding treatment strategies and patient counseling. Methods: We propose a novel hybrid deep learning framework that integrates volumetric MRI-derived imaging biomarkers with structured clinical and demographic data to predict overall survival time. Our dataset includes 148 patients from three institutions, featuring expert-annotated segmentations of enhancing tumors, necrosis, and peritumoral edema. Two convolutional neural network backbones—ResNet-50 and EfficientNet-B0—were fused with fully connected layers processing tabular data. Models were trained using mean squared error loss and evaluated through stratified cross-validation and an independent held-out test set. Results: The hybrid model based on EfficientNet-B0 achieved state-of-the-art performance, attaining an R² score of 0.970 and a mean absolute error of 3.05 days on the test set. Permutation feature importance highlighted edema-to-tumor ratio and enhancing tumor volume as the most informative predictors. Grad-CAM visualizations confirmed the model’s attention to anatomically and clinically relevant regions. Performance consistency across validation folds confirmed the framework’s robustness and generalizability. Conclusions: This study demonstrates that multimodal deep learning can deliver accurate, explainable, and clinically actionable survival predictions in brain metastases. The proposed framework offers a promising foundation for integration into real-world oncology workflows to support personalized prognosis and informed therapeutic decision-making. Full article

Distributed Acoustic Sensing (DAS) systems face increasing challenges in massive data processing and real-time fault diagnosis due to the growing complexity of industrial environments and data volume. To address these issues, an end-to-end diagnostic framework is developed, integrating Mel-Frequency Cepstral Coefficients (MFCCs) for high-efficiency signal compression and Liquid Neural Networks (LNNs) for lightweight, real-time classification. The MFCC algorithm, originally used in speech processing, is adapted to extract key features from DAS vibration signals, achieving compression ratios of 60–100× without significant information loss. LNNs’ dynamic topology and sparse activation enable high accuracy with extremely low latency and minimal computational cost, making it highly suitable for edge deployment. The proposed framework was validated both in simulated environments and on a real-world conveyor belt system at Qinhuangdao Port, where it achieved 100% accuracy across four vibration modes over 14 weeks of operation. Comparative experiments show that LNNs outperform traditional models such as 1D-CNN and LSTMs in terms of accuracy, inference speed, and model size. The proposed MFCC-LNN pipeline also demonstrates strong cross-domain generalization capabilities in pipeline monitoring, seismic detection, and speech signal processing. Full article