Search Results (731)

Extreme surface winds and wave heights of tropical cyclones (TCs)—pose serious threats to coastal community, infrastructure and environments. In recent decades, progress in numerical wave modeling has significantly enhanced the ability to reconstruct and predict wave behavior. This review offers an in-depth overview of TC-related wave modeling utilizing different computational schemes, with a special attention to WAVEWATCH III (WW3) and Simulating Waves Nearshore (SWAN). Due to the complex air–sea interactions during TCs, it is challenging to obtain accurate wind input data and optimize the parameterizations. Substantial spatial and temporal variations in water levels and current patterns occurs when coastal circulation is modulated by varying underwater topography. To explore their influence on waves, this study employs a coupled SWAN and Finite-Volume Community Ocean Model (FVCOM) modeling approach. Additionally, the interplay between wave and sea surface temperature (SST) is investigated by incorporating four key wave-induced forcing through breaking and non-breaking waves, radiation stress, and Stokes drift from WW3 into the Stony Brook Parallel Ocean Model (sbPOM). 20 TC events were analyzed to evaluate the performance of the selected parameterizations of external forcings in WW3 and SWAN. Among different nonlinear wave interaction schemes, Generalized Multiple Discrete Interaction Approximation (GMD) Discrete Interaction Approximation (DIA) and the computationally expensive Wave-Ray Tracing (WRT) A refined drag coefficient (C_d) equation, applied within an upgraded ST6 configuration, reduce significant wave height (SWH) prediction errors and the root mean square error (RMSE) for both SWAN and WW3 wave models. Surface currents and sea level variations notably altered the wave energy and wave height distributions, especially in the area with strong TC-induced oceanic current. Finally, coupling four wave-induced forcings into sbPOM enhanced SST simulation by refining heat flux estimates and promoting vertical mixing. Validation against Argo data showed that the updated sbPOM model achieved an RMSE as low as 1.39 m, with correlation coefficients nearing 0.9881. Full article

With the increasing frequency of marine activities, the significance of underwater target search and rescue has been highlighted, where precise and efficient path planning is critical for ensuring search effectiveness. This study proposes an underwater target search path planning method by incorporating the dynamic variations of marine acoustic environments driven by sea surface wind fields. First, wind-generated noise levels are calculated based on the sea surface wind field data of the mission area, and transmission loss is solved using an underwater acoustic propagation ray model. Then, a spatially variant search distance matrix is constructed by integrating the active sonar equation. Finally, a sixteen-azimuth path planning model is established, and a hybrid algorithm of quantum-behaved particle swarm optimization and tabu search (QPSO-TS) is introduced to optimize the search path for maximum coverage. Numerical simulations in three typical sea areas (the South China Sea, Atlantic Ocean, and Pacific Ocean) demonstrate that the optimized search coverage of the proposed method increases by 54.40–130.13% compared with the pre-optimization results, providing an efficient and feasible solution for underwater target search. Full article

Background/Objectives: Tegoprazan (TPZ) is a potassium-competitive acid blocker (P-CAB) used to treat conditions such as gastroesophageal reflux disease, peptic ulcer, and Helicobacter pylori infection. It exists in three solid forms: amorphous, Polymorph A, and Polymorph B. This study investigates the molecular basis of polymorph selection, focusing on conformational bias and solvent-mediated phase transformations (SMPTs). Methods: The conformational energy landscapes of two TPZ tautomers were constructed using relaxed torsion scans with the OPLS4 force field and validated by nuclear Overhauser effect (NOE)-based nuclear magnetic resonance (NMR). Hydrogen-bonded dimers were analyzed using DFT-D. Powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), solubility, and slurry tests were conducted using methanol, acetone, and water. Kinetic profiles were modeled with the Kolmogorov–Johnson–Mehl–Avrami (KJMA) equation. Results: Polymorph A was thermodynamically stable across all analyses. Both amorphous TPZ and Polymorph B converted to A in a solvent-dependent manner. Methanol induced direct A formation, while acetone showed a B → A transition. Crystallization was guided by solution conformers and hydrogen bonding. Conclusions: TPZ polymorph selection is governed by solution-phase conformational preferences, tautomerism, and solvent-mediated hydrogen bonding. DFT-D and NMR analyses showed that protic solvents favor the direct crystallization of stable Polymorph A, while aprotic solvents promote the transient formation of metastable Polymorph B. Elevated temperatures and humidity accelerate polymorphic transitions. This crystal structure prediction (CSP)-independent strategy offers a practical framework for rational polymorph control and the mitigation of disappearing polymorph risks in tautomeric drugs. Full article

This study systematically investigates the impact of hydrolytic degradation on the crystallization kinetics and morphology of poly(butylene succinate-co-adipate) (PBSA). Gel Permeation Chromatography (GPC) confirmed extensive chain scission, significantly reducing the polymer’s weight-average molecular weight (M_w from ~103,000 to ~16,000 g/mol) and broadening its polydispersity index (PDI from ~2 to 7 after 64 days). Differential scanning calorimetry (DSC) analysis revealed that hydrolytic degradation dramatically accelerated crystallization rates, reducing crystallization time roughly 10-fold (e.g., from ~3000 s to ~300 s), and crystallinity increased from 34% to 63%. Multiple melting peaks suggested the presence of lamellae with varying thicknesses, consistent with the Gibbs–Thomson equation. Isothermal crystallization kinetics were evaluated using the Avrami equation (with n ≈ 3), reciprocal half-time of crystallization, and a novel inflection point slope method, all confirming accelerated crystallization; for instance, the slope increased from 0.00517 to 0.05203. Polarized optical microscopy (POM) revealed evolving spherulite morphologies, including hexagonal and flower-like dendritic spherulites with diamond-shape ends, while wide-angle X-ray diffraction (WAXD) showed a crystallization range shift to higher temperatures (e.g., from 72–61 °C to 82–71 °C) and a 14% increase in crystallite diameter, aligning with increased melting point and lamellar thickness and overall increased crystallinity. Full article

The one-dimensional ray equation, the differential description of Fermat’s principle, is deduced directly from Snell’s law using two methods. In the first method, we obtain the ray equation from a differential equation relating the spatial coordinates derivative with the index of refraction field. In the second method, the ray equation is deduced from the proper generalization of Snell’s law for a refractive field, that is, a differential equation relating the index of refraction field and the refraction angle. Additionally, we used an intermediate expression of the first method to find a straightforward analytical solution of the ray path to an inferior mirage. Full article

This study reports the synthesis and characterization of Co_xNi_1−xFe₂O₄ (x = 0, 0.2, 0.4, 0.6, 0.8, 1) nanoparticles using a co-precipitation method. In this approach, metal ions are precipitated in the presence of a stabilizing agent, which is a common and effective method for nanoparticle preparation. The microstructure and magnetic properties were studied after calcination at 600 °C and heat treatment at 1000 °C. X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy confirmed the formation of a single-phase spinel structure. The average crystallite size, calculated using the (311) diffraction peak and the Scherrer equation, ranged from 13 to 19 nm. Scanning electron microscopy (SEM) showed that the nanoparticles had a spherical morphology. Thermogravimetric and differential thermal analysis (TG-DTA) revealed a three-step weight loss process. Magnetic measurements, including remanent magnetization, saturation magnetization, and coercivity, were performed using a vibrating sample magnetometer (VSM) at room temperature. The replacement of Ni²⁺ with Co²⁺ enhanced the magnetic properties, resulting in increased magnetic moment and anisotropy. These effects are attributed to changes in cation distribution, exchange interactions, surface effects, and magnetocrystalline anisotropy. Overall, Co²⁺ doping improved the magnetic behavior of nickel ferrite, indicating its potential for application in memory devices and magnetic recording media. Full article

Arginine plays a critical role in biomolecular interactions due to its guanidinium side chain, which enables multivalent electrostatic and hydrogen bonding contacts. In this study, atomistic molecular dynamics simulations were conducted across a broad concentration range (26–605 mM) to investigate the thermodynamic and structural features of arginine self-assembly in aqueous solution. Key observables—including hydrogen bond count, radius of gyration, contact number, and isobaric heat capacity—were analyzed to characterize emergent behavior. A three-regime aggregation pattern (dilute, cooperative, and saturated) was identified and quantitatively modeled using the Hill equation, revealing a non-linear transition in clustering behavior. Spatial analyses were supplemented with trajectory-based clustering and radial distribution functions. The heat capacity peak observed near 360 mM was interpreted as a thermodynamic signature of hydration rearrangement. Trajectory analyses utilized both GROMACS tools and the MDAnalysis library. While force field limitations and single-replica sampling are acknowledged, the results offer mechanistic insight into how arginine concentration modulates molecular organization—informing the understanding of biomolecular condensates, protein–nucleic acid complexes, and the design of functional supramolecular systems. The findings are in strong agreement with experimental observations from small-angle X-ray scattering and differential scanning calorimetry. Overall, this work establishes a cohesive framework for understanding amino acid condensation and reveals arginine’s concentration-dependent behavior as a model for weak, reversible molecular association. Full article

In this study, we propose a self-adaptive weighted multi-mineral inversion model (SQP_AW) based on Sequential Quadratic Programming (SQP) and the Adam optimization algorithm for the accurate evaluation of mineral content in carbonate reservoir rocks, addressing the high costs of traditional experimental methods and the strong parameter dependence in geophysical inversion. The model integrates porosity curves (compensated density, compensated neutron, and acoustic time difference), elastic modulus parameters (shear and bulk moduli), and nuclear magnetic porosity data for the construction of a multi-dimensional linear equation system, with calibration coefficients derived from core X-ray diffraction (XRD) data. The Adam algorithm dynamically optimizes the weights, solving the overdetermined equation system. We applied the method to the Asmari Formation in the M oilfield in the Middle East with 40 core samples for calibration, achieving a 0.91 fit with the XRD data. For eight additional uncalibrated samples from Well A, the fit reaches 0.87. With the introduction of the elastic modulus and nuclear magnetic porosity, the average relative error in mineral content decreases from 9.45% to 6.59%, and that in porosity estimation decreases from 8.1% to 7.1%. The approach is also scalable to elemental logging data, yielding inversion precision comparable to that of commercial software. Although the method requires a complete set of logging data and further validation of regional applicability for weight parameters, in future research, transfer learning and missing curve prediction could be incorporated to enhance its practical utility. Full article

This study systematically investigates the magnetic ordering and magnetocaloric properties of a series of polycrystalline compounds, Gd_1-xDy_xScO₃ (x = 0, 0.1, 0.2 and 1). X-ray powder diffraction (XRD) analysis confirms that all samples exhibit an orthorhombic perovskite structure with a space group of Pbnm. The zero-field cooling and field cooling magnetization curves demonstrate a transition from antiferromagnetic to paramagnetic phases, with Néel temperatures of about 3 K for GdScO₃ and 4 K for DyScO₃. The doping of Dy³⁺ weakened long-range antiferromagnetic order and enhanced short-range magnetic disorder in GdScO₃, leading to vanished antiferromagnetic transition between 2 and 100 K for the sample of x = 0.2. Using the Arrott–Noakes equation, we constructed Arrott plots to analyze the system’s critical behavior. Both the compounds with x = 0.1 and x = 0.2 conform to the 3D-Heisenberg model. These results indicate the weakened long-range antiferromagnetic order induced by Dy³⁺ doping. Significant maximal magnetic entropy change (−Δ$S_{\mathrm{M}}^{\mathrm{M}\mathrm{a}\mathrm{x}}$) of 36.03 J/kg K at 3 K for the sample Gd_0.9Dy_0.1ScO₃ is achieved as the magnetic field changes from 0 to 50 kOe, which is higher than that of GdScO₃ (−Δ$S_{\mathrm{M}}^{\mathrm{M}\mathrm{a}\mathrm{x}}$ = 34.32 J/kg K) and DyScO₃ (−Δ$S_{\mathrm{M}}^{\mathrm{M}\mathrm{a}\mathrm{x}}$ = 15.63 J/kg K). The considerable magnetocaloric effects (MCEs) suggest that these compounds can be used in the development of low-temperature magnetic refrigeration materials. Full article

Clay minerals are promising candidates for caffeine removal due to their environmental friendliness and natural abundance. In this study, a commercially available bentonite was modified by Na⁺ exchange and characterized using Fourier transform infrared spectroscopy, X-ray diffractometry, scanning electron microscopy, zeta potential measurements, and specific surface area analysis. Caffeine adsorption was rapid, reaching equilibrium within 15 min. Adsorption isotherms for caffeine and its metabolites (theobromine, paraxanthine, and theophylline) in pure water were analyzed at 25.0 ± 0.5 °C using Langmuir and Freundlich models, both individually and in mixtures. Only caffeine exhibited favorable adsorption behavior, fitting the Langmuir equation, which allowed for the determination of a maximum adsorption capacity of 20 ± 3 mg/g, regardless of metabolite presence. The removal exceeded 85% of the caffeine from a 5.0 mg/L solution. The adsorption affinity of the studied compounds toward Na⁺-exchanged bentonite followed the order: caffeine >>> theobromine > paraxanthine ~ theophylline. The modified bentonite was then tested for caffeine removal from beverages and synthetic urine, achieving removal efficiencies exceeding 87%. To our knowledge, this is the first study investigating the effect of major caffeine metabolites on adsorption rates across different sample matrices, such as artificial urine, cola soda, soluble coffee, energy drinks, green tea, and yerba mate. Full article

In 2019, the Event Horizon Telescope (EHT) released the first image of a black hole, sparking huge interest in the study of black-hole images. We present analytical solutions to the null geodesic equations for Kerr–Newman–de Sitter black holes derived using Jacobi elliptic functions. Using these solutions, we have performed an analytic ray-tracing simulation to model direct images, lensing rings, and photon rings, considering standard observers and zero angular momentum observers (ZAMOs). Additionally, we have derived analytic expressions for the critical parameters governing the structure of the photon ring and analyzed them in detail. From the foregoing, an increase in charge leads to a decrease in both time delay and Lyapunov exponent, while the change in azimuthal angle is insignificant. These findings improve our understanding of the effects of charge on black-hole photon rings and provide a foundation for future studies. Full article

The combination of the catalytic properties of Al₂O_3/TiO₂ formed an efficient system to degrade the ubiquitous pollutants TPA and PET. The coating (Al₂O₃)_0.75TiO₂ was characterized by X-ray diffraction. Stainless steel disks with photo-catalyst coating were placed transversely in a 3.0 L vertical glass reactor with ascending airflow for supplying oxygen to the reaction medium and visible light lamps for photo-activation. The analysis of the coating homogeneity, morphology and particle size distribution of the TiO₂ coatings and (Al₂O₃)_0.75TiO₂ system were confirmed by SEM. Optical properties and band-gap energy were calculated by using the Tauc equation. UV–Vis spectrophotometry (UV–Vis) and chemical oxygen demand (COD) were the quantitative techniques to measure the reduction in the initial TPA and PET concentrations. Full article

Semisteel is the byproduct of the titania slag smelting process of ilmenite concentrate with an electric furnace. To enhance the added value of semisteel, a centrifugal granulation–water curtain process was adopted to manufacture iron powders. The oxidation characteristics of granulated powders were analyzed by thermogravimetry (TG), X-ray diffraction (XRD), and scanning electron microscopy (SEM). To obtain iron powders with high purity, the isothermal oxidation kinetics of pure iron powders under vapor atmosphere were studied. TG measurements of pure iron powders were conducted at 1073 K, 1173 K, and 1273 K using a humidity generating instrument and a thermal analyzer. The results indicate that the oxidation rate increases with the increasing temperature and decreasing powder size. The entire isothermal oxidation process of iron powders with different sizes (0.3 mm < d₁ < 0.35 mm, 0.4 mm < d₂ < 0.45 mm, and 0.5 mm < d₃ < 0.55 mm) comprises two stages. The first oxidation stage is controlled by chemical reaction; the second oxidation stage is controlled by both internal diffusion and chemical reaction. The activation energies and oxidation reaction rate equations of iron powders at different stages are calculated. Full article

The article presents research on the application of computed tomography with an incomplete dataset to the problem of examining the internal structure of walls. The case of incomplete information in computed tomography often occurs in various applications, e.g., when examining large objects or when examining hard-to-reach objects. Algorithms dedicated to this type of problem can be used to detect anomalies (defects, cracks) in the walls, among other artifacts. Situations of this type may occur, for example, in old buildings, where special caution should be exercised. The approach presented in the article consists of a non-standard solution to the problem of reconstructing the internal structure of the tested object. The classical approach involves constructing an appropriate system of equations based on X-rays, the solution of which describes the structure. However, this approach has a drawback: solving such systems of equations is computationally very complex, because the algorithms used, combined with incomplete information, converge very slowly. In this article, we propose a different approach that eliminates this problem. To simulate the structure of the tested object, we use a hybrid algorithm that is a combination of a metaheuristic optimization algorithm (Group Teaching Optimization Algorithm) and a numerical optimization method (Hook-Jeeves method). In order to solve the considered inverse problem, a functional measuring the fit of the model to the measurement data is created. The hybrid algorithm presented in this paper was used to find the minimum of this functional. This paper also shows computational examples illustrating the effectiveness of the algorithms. Full article

The reduction of graphene oxide (GO) is critical for tuning its properties. This study integrates optical contrast analysis with Raman spectroscopy and X-ray photoelectron spectroscopy (XPS) to investigate the structural and optical evolution of GO in thermal reduction. For GO on 100 nm SiO₂/Si, the R channel contrast exhibits superior sensitivity to structural changes, making it a reliable indicator of the reduction process. A theoretical model based on Fresnel equations reveals the role of SiO₂ thickness in modulating optical contrast, providing guidelines for substrate optimization and channel selection. Full article