Search Results (1,582)

The aim of this study was to address the issue of significant performance degradation in existing defogging algorithms under extreme fog conditions. Traditional Taylor series-based deformable convolutions are limited by local approximation errors, while the heavy-tailed characteristics of the Cauchy distribution can more successfully model outliers in fog images. The following improvements are made: (1) A displacement generator based on the inverse cumulative distribution function (ICDF) of the Cauchy distribution is designed to transform uniform noise into sampling points with a long-tailed distribution. A novel double-peak Cauchy ICDF is proposed to dynamically balance the heavy-tailed characteristics of the Cauchy ICDF, enhancing the modeling capability for sudden changes in fog concentration. (2) An innovative Cauchy–Gaussian fusion module is proposed to dynamically learn and generate hybrid coefficients, combining the complementary advantages of the two distributions to dynamically balance the representation of smooth regions and edge details. (3) Tree-based multi-path and cross-resolution feature aggregation is introduced, achieving local–global feature adaptive fusion through adjustable window sizes (3/5/7/11) for parallel paths. Experiments on the RESIDE dataset demonstrate that the proposed method achieves a 2.26 dB improvement in the peak signal-to-noise ratio compared to that obtained with the TaylorV2 expansion attention mechanism, with an improvement of 0.88 dB in heavily hazy regions (fog concentration > 0.8). Ablation studies validate the effectiveness of Cauchy distribution convolution in handling dense fog and conventional lighting conditions. This study provides a new theoretical perspective for modeling in computer vision tasks, introducing a novel attention mechanism and multi-path encoding approach. Full article

Unconventional oil reservoirs are tight and often host micro-nano pores, and huff and puff is usually adopted for such reservoirs, mainly utilizing the mechanism of spontaneous imbibition. The penetration depth into the matrix during imbibition is one of the key influencing factors of oil recovery. In circumstances where a water phase is present in the reservoir, the injected oil displacement agent may not directly contact the oil phase, but instead needs to diffuse and migrate to the oil–water interface to adjust the capillary force, thereby affecting the imbibition depth. Therefore, the diffusion law of the oil displacement agent can indirectly affect the oil recovery by imbibition. In this study, microfluidic experiments were conducted to investigate the diffusion of nano oil displacement agents at different pore sizes (100 μm). The results show that the concentration distribution of nano oil displacement agents near the injection end was uniform during the diffusion process, and the concentration showed a decreasing trend with increasing depth. As the pore size decreased, the diffusion coefficient also decreased, and the diffusion effect deteriorated. There was a lower limit of pore size that allowed diffusion at approximately 15.66 μm. The diffusion law of the nano oil displacement agent in porous media obtained in this study is of great significance for improving the recovery rate of unconventional oil and gas resources. Full article

A facile and cost-effective sol–gel method for the synthesis of uniformly porous alumina (Al₂O₃) was developed using stable CTAB/hexanol/water microemulsions as soft templates. The phase behavior of the ternary system was investigated to identify compositions that form kinetically stable microemulsions, with an optimal ratio of 7.5 wt.% CTAB, 5 wt.% hexanol, and 87.5 wt.% water exhibiting minimal droplet size variation over one week. Gelation was induced by partial neutralization to pH 4.2 with ammonium carbonate, promoting the formation of polynuclear Al species and enabling the uniform entrapment of hexanol droplets. Lyophilization preserved the porous network, and calcination at 500 °C yielded η-Al₂O₃ with a large specific surface area (~225 m²·g⁻¹) and a narrow mesopore size distribution centered around 100 nm, consistent with the original droplet size. Mercury porosimetry and SEM analyses confirmed a highly porous, low-density material (0.75 g·cm⁻³) with an interconnected pore morphology. This scalable synthesis method, supported by the high kinetic stability of the microemulsion, provides sufficient processing time and eliminates the need for post-synthesis purification. It shows strong potential for producing advanced alumina materials for use in energy storage, catalysis, and sensor applications. Full article

Porous carbon-loaded MnO was prepared via a combination of the sol–gel method and the chemical blow molding method using polyvinylpyrrolidone (PVP) and manganese nitrate as starting materials. SEM, EDX, TEM, FTIR, XRD, XPS, nitrogen adsorption–desorption, and elemental analysis were used to assess its physical and chemical characteristics. Furthermore, the adsorption property of porous carbon-loaded MnO for hexavalent chromium (Cr(VI)) in polluted water was investigated in detail. The results demonstrated that large numbers of MnO nanoparticles were evenly mounted on the surfaces of carbon walls, with a uniform distribution of C, N, and O elements. The BET surface area was 46.728 m²/g, and the pore sizes of porous carbon ranged from 2 nm to 10 nm. Additionally, abundant surface functional groups were found in porous carbon-loaded MnO, a result consistent with XPS data and applicable to the adsorption of heavy metals from aqueous solutions containing Cr(VI). The Freundlich model fitted the adsorption isotherm well, and the pseudo−second−order model precisely matched the adsorption kinetics. According to the study results, the adsorption was multilayer, and the adsorption process involved an endothermic reaction. These results indicate that this is a feasible way to synthesize a high−efficiency adsorbent for the removal of harmful heavy−metal ions from wastewater. Full article

To improve the mechanical stability and service durability of solar road structures, this study systematically investigates the mechanical response characteristics of photovoltaic panels with different geometric shapes—including triangles, rectangles, squares, regular pentagons, and regular hexagons—under consistent boundary and loading conditions using the discrete element method (DEM). All panels have a uniform thickness of 10 cm and equivalent surface areas to ensure shape comparability. Side lengths vary among the shapes: square panels with sides of 0.707 m, 1.0 m, and 1.5 m; triangle 1.155 m; rectangle (aspect ratio 1:2) 0.707 m; pentagon 1.175 m; and hexagon 0.577 m. Results show that panel geometry significantly influences stress distribution and deformation behavior. Although triangular panels exhibit higher ultimate bearing capacity and failure energy, they suffer from severe stress concentration and low stiffness. Regular hexagonal panels, due to their geometric symmetry, enable more uniform stress and displacement distributions, offering better stability and crack resistance. Size effect analysis reveals that larger panels improve load-bearing and energy dissipation capacity but exacerbate edge stress concentration and reduce overall stiffness, leading to more pronounced “thinning” deformation and premature failure. Failure mode analysis further indicates that shape governs crack initiation and path, while size determines crack propagation rate and failure extent—revealing a coupled shape–size mechanical mechanism. Regarding assembly, honeycomb arrangements demonstrate superior mechanical performance due to higher compactness and better load-sharing characteristics. The study ultimately recommends the use of small-sized regular hexagonal units and optimized splicing structures to balance strength, stiffness, and durability. These findings provide theoretical guidance and parameter references for the structural design of solar roads. Full article

Solvent-exchange-induced in situ forming gel (ISG) refers to a drug delivery system that transforms from a solution state into a gel or solid matrix upon administration into the body and exposure to physiological aqueous fluid. This study investigates the molecular behavior and phase inversion process of cellulose acetate butyrate (CAB)-based in situ forming gel (ISG) formulations containing moxifloxacin (Mx) or benzydamine HCl (Bz) as model drugs dissolved in N-methyl pyrrolidone (NMP) using molecular dynamics (MD) simulations and density functional theory (DFT) calculations. The simulations reveal a solvent exchange mechanism, where the diffusion of water molecules replaces NMP, driving the formation of the CAB matrix. Bz exhibited faster diffusion and a more uniform distribution compared to Mx, which aggregated into clusters due to its larger molecular size. The analysis of the root mean square deviation (RMSD) and radius of gyration confirmed the faster diffusion of Bz, which adopted a more extended conformation, while Mx remained compact. The phase transformation was driven by the disruption of CAB-NMP hydrogen bonds, while CAB–water interactions remained limited, suggesting that CAB does not dissolve in water, facilitating matrix formation. The molecular configuration revealed that drug–CAB interactions were primarily governed by hydrophobic forces and van der Waals interactions rather than hydrogen bonding, controlling the release mechanism of both compounds. DFT calculations and electrostatic potential (ESP) maps illustrated that the acetyl group of CAB played a key role in drug–polymer interactions and that differences in CAB substitution degrees influenced the stability of drug-CAB complexes. Formation energy calculations indicated that Mx-CAB complexes were more stable than Bz-CAB complexes, resulting in a more prolonged release of Mx compared to Bz. Overall, this study provides valuable insights into the molecular behavior of CAB-based Mx-, Bz-ISG formulations. Full article

In deep shale gas fracturing, the narrow width of micro fractures presents a challenge for conventional proppants (40/70 mesh, 70/140 mesh), which often fail to enter branch fractures, resulting in inadequate effective support volume. To address this, a high-efficiency propping strategy is proposed based on the hybrid use of micro-proppants and conventional proppants. Utilizing a proppant transport experiment device, the effects of proppant size ratios and injection timing on proppant distribution were investigated to determine the optimal design parameters. The results indicate that the 200/400 mesh micro-proppant can effectively enter the distal micro fractures, thereby mitigating the problem of the non-uniform distribution of the proppant within the fracture network. To ensure effective propping of secondary fractures, the optimal pumping sequence is to inject quartz sand first, followed by ceramic proppants. The recommended ratio of 70/140 mesh quartz sand to 40/70 mesh ceramic proppants is 7:3. Additionally, for blended injection, the optimal mixing ratio of 70/140 mesh quartz sand to micro-proppant is 8:2. Field trials at the L-X1 well in the LZ block demonstrate that this strategy significantly boosts post-fracturing production, with test yields increasing 2.4 to 4 times. Full article

Three-dimensional trench electrode silicon detectors play an important role in particle physics research, nuclear radiation detection, and other fields. A novel polysilicon-fill-strengthened etch-through 3D trench electrode detector is proposed to address the shortcomings of traditional 3D trench electrode silicon detectors; for example, the distribution of non-uniform electric fields, asymmetric electric potential, and dead zone. The physical properties of the detector have been extensively and systematically studied. This study simulated the electric field, potential, electron concentration distribution, complete depletion voltage, leakage current, capacitance, transient current induced by incident particles, and weighting field distribution of the detector. It also systematically studied and analyzed the electrical characteristics of the detector. Compared to traditional 3D trench electrode silicon detectors, this new detector adopts a manufacturing process of double-side etching technology and double-side filling technology, which results in a more sensitive detector volume and higher electric field uniformity. In addition, the size of the detector unit is 120 µm × 120 µm × 340 µm; the structure has a small fully depleted voltage, reaching a fully depleted state at around 1.4 V, with a saturation leakage current of approximately $4.8\times {10}^{-10}\mathrm{A}$, and a geometric capacitance of about 99 fF. Full article

This study evaluates the applicability and accuracy of coarse-grain modeling (CGM) in discrete-element method (DEM)–based simulations, focusing on particle-mixing efficiency in five representative industrial mixers: the tumbling V mixer, ribbon-blade mixer, paddle-blade mixer, vertical-blade mixer, and conical-screw mixer. Although the DEM is widely employed for particulate system simulations, the high computational cost associated with fine particles significantly hinders large-scale applications. CGM addresses these issues by scaling up particle sizes, thereby reducing particle counts and allowing longer simulation timesteps. We utilized the Lacey mixing index (LMI) as a statistical measure to quantitatively assess mixing uniformity across various CGM scaling factors. Based on the results, CGM significantly reduced computational time (by over 90% in certain cases) while preserving acceptable accuracy levels in terms of LMI values. The mixing behaviors remained consistent under various CGM conditions, based on both visually inspected particle distributions and the temporal LMI trends. Although minor deviations occurred in early-stage mixing, these discrepancies diminished with time, with the final LMI errors remaining below 5% in most scenarios. These findings indicate that CGM effectively enhances computational efficiency in DEM simulations without significantly compromising physical accuracy. This research provides practical guidelines for optimizing industrial-scale particle-mixing processes and conducting computationally feasible, scalable, and reliable DEM simulations. Full article

This study investigates the thermal stability and microstructural evolution of the solid electrolyte medium used in DLyte^® dry electropolishing and dry anodizing processes. Samples were thermally aged between 30 °C and 45 °C to simulate Joule heating during industrial operation. Visual and SEM analyses revealed shape deformation and microcrack formation at temperatures above 40 °C, potentially reducing particle packing efficiency and electrolyte performance. Particle size distribution shifted from bimodal to trimodal upon aging, with an overall size reduction of up to 39.5% due to dehydration effects, impacting ionic transport properties. Weight-loss measurements indicated a diffusion-limited dehydration mechanism, stabilizing at 15–16% mass loss. Fourier transform infrared analysis confirmed water removal while maintaining the essential sulfonic acid groups responsible for ionic conductivity. In dry anodizing tests on titanium, aged electrolytes enhanced process efficiency, producing TiO₂ films with improved optical properties—color and brightness—while preserving thickness and uniformity (~70 nm). The results highlight the need to carefully control thermal exposure to maintain electrolyte integrity and ensure consistent process performance. Full article

As the core equipment for efficient wastewater treatment, the internal structure of microporous aeration bioreactors directly determines the mass transfer efficiency and treatment performance. Based on Computational Fluid Dynamics (CFD) technology, this study explores the optimization mechanism of a Spherical Grid-Structured on the internal flow field of the reactor through a 3D numerical simulation system, aiming to improve the aeration efficiency and resource utilization. This study used a combination of experimental and numerical simulations to compare and analyze different configurations of the Spherical Grid-Structure. The simulation results show that the optimal equilibrium of the flow field inside the reactor is achieved when the diameter of the grid sphere is 2980 mm: the average flow velocity is increased by 22%, the uniformity of the pressure distribution is improved by 25%, and the peak turbulent kinetic energy is increased by 30%. Based on the Kalman vortex street theory, the periodic vortex induced by the grid structure refines the bubble size to 50–80 microns, improves the oxygen transfer efficiency by 20%, increases the spatial distribution uniformity of bubbles by 35%, and significantly reduces the dead zone volume from 28% to 16.8%, which is a decrease of 40%. This study reveals the quantitative relationship between the structural parameters of the grid and the flow field characteristics through a pure numerical simulation, which provides a theoretical basis and quantifiable optimization scheme for the structural design of the microporous aeration bioreactor, which is of great significance in promoting the development of low-energy and high-efficiency wastewater treatment technology. Full article

Due to the limitations of high speed and short time in plasma-spraying experiments, this study established a simulation model of Y₂O₃ multi-particle deposition to discuss the influence of laser loading on coating-deposition behavior and performance. According to the simulation results, the temperature of coating particles under laser loading displays a gradient distribution, with the surface having the highest temperature. The particles deposit on the substrate to form uniform pits of a certain depth. Plastic deformation causes maximum stress to occur at the edges of the pits and maximum strain to occur on the sidewall of the pits. The deposition region had both compressive and tensile stresses, and laser loading greatly reduced the tensile stresses’ magnitude while having less of an impact on the particle strains. Laser assistance promotes further melting of particles, reduces coating thickness, lowers coating porosity to 3.94%, increases hardness to 488 MPa, reduces maximum pore size from 68 µm to 32 µm, and causes particle sputtering to gradually evolve from being disc-shaped to being finger-shaped, creating cavities at the coating edges. The comparison between the surface morphology and the cross-section pores of the experimentally prepared coating verified the rationality and viability of the simulation work. Full article

Chaotic systems have demonstrated significant potential in the field of image encryption due to their extreme sensitivity to initial conditions, inherent unpredictability, and pseudo-random behavior. However, existing chaos-based encryption schemes still face several limitations, including narrow chaotic regions, discontinuous chaotic ranges, uneven trajectory distributions, and fixed pixel processing sequences. These issues substantially hinder the security and efficiency of such algorithms. To address these challenges, this paper proposes a novel hyperchaotic map, termed the two-dimensional cross-coupled chaotic map (2D-CFCM), derived from a newly designed 2D cross-coupled chaotic system. The proposed 2D-CFCM exhibits enhanced randomness, greater sensitivity to initial values, a broader chaotic region, and a more uniform trajectory distribution, thereby offering stronger security guarantees for image encryption applications. Based on the 2D-CFCM, an innovative image encryption method was further developed, incorporating efficient scrambling and forward and reverse random multidirectional diffusion operations with symmetrical properties. Through simulation tests on images of varying sizes and resolutions, including color images, the results demonstrate the strong security performance of the proposed method. This method has several remarkable features, including an extremely large key space (greater than $2^{912}$), extremely high key sensitivity, nearly ideal entropy value (greater than 7.997), extremely low pixel correlation (less than 0.04), and excellent resistance to differential attacks (with the average values of NPCR and UACI being $99.6050\%$ and $33.4643\%$, respectively). Compared to existing encryption algorithms, the proposed method provides significantly enhanced security. Full article

To investigate the effect of liquid-phase laser ablation on the hardness of WC-Co cemented carbide, this study performed hardness testing, elemental distribution analysis, and XRD phase analysis. The influence of ablation times on the hardness, elemental distribution, and phase composition of WC-Co cemented carbide was examined, and a model describing the hardness evolution mechanism under liquid-phase laser ablation was proposed. The results demonstrated that the hardness of WC-Co cemented carbide increased with the number of ablations. After 14 ablation times, the maximum hardness reached 2800 HV, representing an increase of 51%–56% compared to the matrix hardness. As the number of ablations increased, the content of ditungsten carbide (W₂C) and tungsten carbide (WC) in the cemented carbide increased, the WC grain size decreased, the dislocation density increased, and the distribution became more uniform. The refinement of WC grains and the elevated dislocation density facilitated stronger intergranular bonding, thereby significantly enhancing the material’s hardness. This study provides theoretical guidance for improving the surface mechanical properties of WC-Co cemented carbide tools through liquid-phase laser ablation. Full article

Network connectivity and area coverage are the most important aspects in the applications of wireless sensor networks (WSNs). The resource and energy constraints of sensor nodes, operational conditions, and network size pose challenges to the optimal coverage of targets in the region of interest (ROI). The main idea is to achieve maximum area coverage and connectivity with strategic deployment and the minimal number of sensor nodes. This work addresses the problem of network area coverage in randomly distributed WSNs and provides an efficient deployment strategy using an enhanced version of cuckoo search optimization (ECSO). The “sequential update evaluation” mechanism is used to mitigate the dependency among dimensions and provide highly accurate solutions, particularly during the local search phase. During the preference random walk phase of conventional CSO, particle swarm optimization (PSO) with adaptive inertia weights is defined to accelerate the local search capabilities. The “opposition-based learning (OBL)” strategy is applied to ensure high-quality initial solutions that help to enhance the balance between exploration and exploitation. By considering the opposite of current solutions to expand the search space, we achieve higher convergence speed and population diversity. The performance of ECSO-OBL is evaluated using eight benchmark functions, and the results of three cases are compared with the existing methods. The proposed method enhances network coverage with a non-uniform distribution of sensor nodes and attempts to cover the whole ROI with a minimal number of sensor nodes. In a WSN with a 100 m² area, we achieved a maximum coverage rate of 98.45% and algorithm convergence in 143 iterations, and the execution time was limited to 2.85 s. The simulation results of various cases prove the higher efficiency of the ECSO-OBL method in terms of network coverage and connectivity in WSNs compared with existing state-of-the-art works. Full article