Search Results (1,591)

Wax deposition occurs to varying degrees in most oil and gas wells. The basic data of existing wax precipitation prediction models are mainly single-component wax experimental data based on the melting process of wax crystals during heating, which is quite different from the cooling crystallization process of wax in oil and gas production. Moreover, the published solubility test data of binary n-alkanes are mainly concentrated in the range of nC10–nC36, leaving existing thermodynamic models without available data for predicting the behavior of high-carbon alkanes. Based on the idea of wax crystallization and precipitation during cooling, this study experimentally determined the solid–liquid equilibrium solubilities of high-carbon n-alkanes (nC38, nC40, nC44, nC48 and nC50) with different concentrations in n-heptane, n-nonane and n-dodecane, as well as the crystallization parameters of pure substances, by using a DSC instrument. This effectively fills the gap in the basic physical property data of long-chain alkanes (more than nC36) and the cooling process in existing studies. In addition, we measured the crystallization parameters of pure high-carbon n-alkanes (nC38, nC40, nC44, nC48 and nC50) during cooling, including crystallization temperature, transition temperature, crystallization enthalpy and transition enthalpy under cooling conditions. The experimental data are in good agreement with the solubility predicted by the ideal solution model for the cooling process, with an average absolute percentage error of less than 10% and average solubility deviation generally within 0.078 mol%. This indicates that the ideal solution model has good accuracy for predicting the precipitation of n-alkane wax and n-alkane solvents. This study provides basic data for the prediction theory of paraffin precipitation. Full article

Fiber interferometers are widely used in precision measurement fields such as seismic observation, gravitational-wave detection, and aerospace guidance. However, phase noise in the Hz–kHz range has become an important factor limiting further improvement in measurement accuracy. In this work, a solid-core photonic crystal fiber (PCF) and a hollow-core photonic bandgap fiber (HC-PBGF) were introduced into the sensing arms of a fiber interferometer to reduce phase noise in this frequency range. Theoretical analysis showed that, compared with a conventional solid-core fiber, the PCF and the 19-cell HC-PBGF used in this study could reduce the phase noise by approximately 3 dB and 7 dB, respectively. The experimental results agreed well with the theoretical predictions, confirming that both fibers can effectively suppress high-frequency phase noise, with HC-PBGF showing superior noise reduction performance. This work provides a feasible approach for improving the performance of fiber interferometers in precision measurement. Full article

A new series of eight novel etodolac-based 1,3,4-oxadiazoles was synthesized, characterized, and tested in silico in multidimensional routes, starting with etodolac, a well-known nonsteroidal anti-inflammatory medication (NSAID). In silico studies were performed prior to synthesis using the molecular docking technique in CCDC GOLD suite software (2025.3) to assess the interactions with two key targets involved in cancer pathogenesis: the crystal structure of the epidermal growth factor receptor EGFR tyrosine kinase domain (PDB ID: 4HJO) and the matrix metalloproteinase (MMP-9) complex (PDB ID: 5CUH). ADME studies were performed to assess the physicochemical properties of the synthesized molecules. Importantly, biotransformation prediction also indicated that the derivatives possess high metabolic stability, with hydroxylation of the thio-ether group as the primary predicted biotransformation route. All compounds were characterized using melting point, FT-IR, ¹H-NMR, and ¹³C-NMR spectroscopy. In vitro and/or in vivo experiments are needed to confirm this preliminary anticancer study. Full article

This study proposes a data-driven framework with post hoc interpretability analysis for one-step-ahead crystal diameter prediction in the Czochralski (CZ) silicon single-crystal growth process. To address the strong multivariable coupling, nonlinear dynamics, variable-specific delays, and difficulty of online measurement in CZ growth, the maximal information coefficient (MIC) was first used to screen key auxiliary variables from industrial process data. The Grey Wolf Optimizer (GWO) was then employed for multi-variable delay estimation and feature alignment, and a hybrid temporal convolutional network (TCN)–long short-term memory (LSTM) model was constructed to combine local temporal feature extraction with long-term dependency learning. Four input configurations were designed according to whether lag alignment and diameter history were included, and the proposed TCN-LSTM was systematically compared with standalone TCN and LSTM models. The results show that both diameter history and delay alignment improve prediction performance. Under the current single-run evaluation protocol, the TCN-LSTM configurations yielded lower prediction errors than the corresponding TCN and LSTM models under the same input settings. Under the withlag-withY configuration, the TCN-LSTM model achieved MSE = 0.00259, RMSE = 0.05087, MAE = 0.03949, and R² = 0.96982. After GWO-based hyperparameter optimization, the best TCN-LSTM configuration further improved to MSE = 0.00239, RMSE = 0.04894, MAE = 0.03651, and R² = 0.97207. SHAP-based analysis was further used to provide a post hoc interpretation of the relative contributions of key process variables to diameter variation. Overall, the proposed framework provides a data-driven prediction approach and may support subsequent process analysis and optimization in industrial CZ growth. Full article

The selection of deformation mechanisms in hexagonal close-packed (HCP) metals is strongly influenced by both crystallographic orientation and macroscopic deformation constraints. In commercially pure titanium, plastic deformation under constrained loading conditions involves a complex interplay between dislocation slip and deformation twinning, whose respective activation cannot be fully described by classical stress-based criteria. In this study, the mechanical origin of slip and twinning variant selection in commercially pure titanium subjected to plane strain compression is investigated experimentally. Plane strain compression is used as a canonical loading condition representative of constrained deformation paths encountered in sheet metal forming. Interrupted in-situ electron backscatter diffraction is combined with slip trace and twin variant analyses to identify the active deformation mechanisms at the grain scale. Resolved shear stress calculations show that stress-based criteria provide a necessary first-order condition for the activation of both slip and twinning systems. While the Schmid factor reasonably predicts part of the observed slip activity, it fails to uniquely determine the selection of active twinning variants. A kinematic analysis reveals that twinning variant selection is governed by the compatibility between the deformation induced by twinning and the macroscopic strain constraints imposed by plane strain compression. Only variants whose deformation accommodates compression along the loading axis, extension along the free in-plane direction, and minimal strain along the constrained in-plane direction are preferentially activated. These results demonstrate that deformation mechanism selection in HCP titanium under constrained loading conditions results from a combined effect of resolved shear stress and kinematic compatibility. The proposed framework provides a physically grounded basis for interpreting deformation-induced texture evolution and offers clear perspectives for the development of crystal plasticity models incorporating twinning under complex strain paths. Full article

This review surveys how nanoparticles and biomolecular nanosized structures interact with model membrane systems, and how these interfacial processes govern their performance in drug and gene delivery, antimicrobial strategies, biosensing, and nanotoxicology. The nanostructures covered include polymeric nanoparticles, lipid-based carriers, peptide nanostructures, dendrimers, and multifunctional hybrids. Model membranes span Langmuir monolayers, supported lipid bilayers, vesicles/liposomes across sizes, and emerging hybrid or asymmetric constructs that better approximate native complexity. Mechanistically, interactions follow recurrent routes—surface adsorption, bilayer insertion, pore formation, and lipid extraction/reorganization—regulated by particle size, morphology, charge, ligand architecture, and lipophilicity, in conjunction with membrane composition, phase state, curvature, and asymmetry. A multiscale toolkit links structure, mechanics, and dynamics: Langmuir troughs and Brewster Angle Microscopy map thermodynamics and mesoscale morphology; atomic force microscopy and quartz crystal microbalance with dissipation resolve nanoscale topography and viscoelasticity; fluorescence microscopy/spectroscopy reports on localization and packing; neutron and X-ray reflectometry quantify vertical structure; molecular dynamics provides atomistic pathways and design hypotheses. Historically, the field advanced from early monolayers and bilayers, through the fluid mosaic model, to raft microdomains and modern biomimetic systems, enabling increasingly realistic experiments. Key advances include cross-method integration linking experimental observations with image-based computational models; persistent debates concern the translation from simplified models to living membranes, the role of dynamic coronas, and scale/force-field limits in simulations. Future efforts should prioritize hybrid models incorporating proteins and asymmetric lipidomes, standardized reporting and reference systems, rigorous coupling of experiments with calibrated simulations and machine learning, and alignment with safety-by-design and regulatory expectations, thereby shifting interfacial measurements from descriptive observation to predictive design rules. Full article

Design and fabrication of high-performance organic semiconductors are still challenging. Here, we designed new D-(A)n type zinc porphyrin end-capped ethynylene-7-(4-hexyl-thiophen-2-yl)-2,1,3-benzothiadiazole (EBTT) oligomers by linking 5,10,15-trisphenyl porphyrin zinc (ZnTPP) with length-variable EBTT oligomers (at the 20-position of porphyrin) [ZnTPP(EBTT)_n (n = 1–6)]. The influence of oligomer length on molecular structures, orbital energies, electronic absorption spectra, ionization energies, electronic affinities, and reorganization energies was systematically studied through density functional theory. The charge-carrier mobility of the simulated crystals and the power conversion efficiencies (PCE) using PCBM as the accepter were also predicted. ZnTPP(EBTT)₆ show excellent hole/electron mobility of 76.161/9.395 cm²V⁻¹s⁻¹ and extremely high PCE of 25.45%. This work would have significance for the design and synthesis of organic semiconductor materials with large charge-carrier mobility and high PCE performance. Full article

The presence of an unbalanced gut microbiome and the dysregulation of bile acid signalling are considered pivotal causes of various inflammation-based diseases. The Takeda G protein-coupled receptor (TGR5), TGR5 is a bile acid-responsive receptor that modulates inflammatory signalling pathways, making it an enticing molecular target for the discovery of novel anti-inflammatory agents. Herein, a comprehensive in silico approach was employed to identify potential TGR5 agonists from sterol-rich phytocompounds present in Triphala, a traditional polyherbal formulation. Using in silico computational methods, such as molecular docking and molecular dynamics simulations (MDS), we screened the putative agonistic potential of 10 phytocompounds obtained from Terminalia chebula, Terminalia bellirica, and Phyllanthus emblica against the crystal structure of human TGR5 (PDB ID: 7XTQ). Based on binding energy and molecular interactions, ergosterol (−12.34 ± 0.17 kcal/mol) and stigmasterol (−10.35 ± 0.04 kcal/mol) were predicted to be the top and best compounds. Furthermore, the stability of these two compounds in the docked complex was analysed using MDS for 200 ns. The mean Cα RMSD values were 0.22 ± 0.02 nm for both ergosterol- and stigmasterol-bound complexes, compared to 0.21 ± 0.02 nm for the unbound apo protein. Further, the molecular mechanics/Poisson–Boltzmann surface area (MMPBSA) analysis revealed that ergosterol exhibited binding free energy (−139.868 ± 12.318 kJ/mol) comparable to that of the co-crystallised ligand R399 −93.424 ± 8.919 kJ/mol. In silico ADMET predictions indicated acceptable drug-like properties and low toxicity for both compounds. Collectively, these computational findings suggest that ergosterol is a promising putative TGR5 agonist, warranting further experimental validation of its potential role in modulating inflammation-related pathways. Full article

Nitridation of different materials using ion implantation is of considerable interest for many applications. As electronic components, oxynitride (SiO_xN_y) layers exhibit beneficial properties such as precise compositional variability, refractive index tunability, oxidation resistance, and low mechanical stress. In the present study we investigate nanoscale SiO_xN_y synthesized using ion implantation methods. To introduce N⁺ ions into a shallow Si subsurface region, both conventional ion beam implantation and plasma immersion ion implantation with subsequent high-temperature treatment in dry O₂ are used. The optical and morphological properties and chemical bonding of formed SiO_xN_y layers were studied by applying spectroscopic ellipsometry in the range of VIS-Near IR (SE) and IR (IR-SE), Raman spectroscopy and Atomic Force Microscopy (AFM). Monte Carlo modeling of implant profiles contributed to understanding physical and chemical processes and predicted different influences of the incorporated N⁺ ions on the oxidation mechanism, confirmed by the thickness dependence of SiO_xN_y/Si layers obtained from the SE data analysis. IR-SE spectral analysis established the formation of Si-O, Si-N, Si-N-O and Si-Si chemical bonds in the grown layers. The occurrence of amorphization of the Si crystal lattice due to incorporation of high-energy N⁺ ions into the Si lattice is confirmed by the Raman and ellipsometry results. The free Si atoms can congregate, forming nanocrystalline clusters. AFM imaging revealed that both implantation methods left the surface of the resulting SiO_xN_y layers considerably smooth with similar roughness parameter values. The results of the studies imply that the technological approaches used allow the production of high-quality nanoscale silicon oxynitride films with appropriate tunable composition and properties for possible application in advanced electronic devices for nanoelectronics, optoelectronics and sensor applications. Full article

This study develops a kinetic model that captures poly-ether-ether-ketone (PEEK) crystallization over a temperature $T$ window from glass transition ($T_g$) to melting ($T_m$) temperature, and across cooling rates from 5 to ~10³ °C/min. The framework is a parallel dual-Nakamura formulation whose isokinetic parameters {$k_i\left(T\right),n_i,w_i\left(T\right)$} are obtained from a bi-level non-linear regression of isothermal crystallization tests conducted using a flash-differential scanning calorimeter (FSC). The weight $w_i\left(T\right)$ partitions the faster primary and slower secondary crystallization and is represented by a physics-based analytical function that captures its dome-shaped temperature dependence. A maximum isothermally achievable enthalpy function is introduced so that the model predicts enthalpy $\Delta H\left(t\right)$ natively under arbitrary thermal profiles. To extend this isothermal backbone to non-isothermal conditions, two explicit cooling-rate-dependent scalars are introduced, $\omega \left(\dot{T}\right)$ and $\chi \left(\dot{T}\right)$, which shift $w_i\left(T\right)$ and limit attainable crystallinity at high cooling rates respectively. Finally, a rate-dependent induction time relation is added to adjust the onset of crystallization. Calibrating these rate functions against non-isothermal experiments, while keeping the isokinetic parameters fixed, yields a single isothermal–non-isothermal model that predicts $\Delta H\left(t\right)$ under arbitrary $T\left(t\right)$ profiles. Model performance is validated using an interrupted FSC experiment with a multi-segment cooling program that mimics a local transient thermal history of PEEK during additive manufacturing. The sample is cooled through successive constant-rate segments with intermittent quench–remelt cycles to probe the accumulated crystallinity along the path. Without additional fitting, the model predicts the measured enthalpy evolution with R² ≈ 0.95. The framework thus provides a practical route for predicting polymer crystallinity under processing-relevant thermal histories. Full article

Nitronyl nitroxides (NNs) are widely employed in chemistry, physics, and materials science due to their inherently high stability and magnetic properties. However, the synthesis of C(2)-organoelement derivatives remains a challenging task. This paper reports on the efficient synthesis and characterization of an unusual organosilver complex consisting of the [Ag–(IPr)₂]⁺ cation and the [Ag–(NN)₂]⁻ anion. The salt [Ag–(IPr)₂][Ag–(NN)₂] was prepared in high yields (88–96%) by two synthetic routes: by reacting the carbene ligand precursor IPr·HCl with Ag₂O and nitronyl nitroxide NN–H, or by addition of NN–H/^tBuONa to a THF solution of IPrAgCl (generated in situ from IPr·HCl and Ag₂O) under microwave irradiation. Electrochemical analysis of [Ag–(IPr)₂][Ag–(NN)₂] revealed a reversible one-electron oxidation peak at E_1/2 = −0.258 V and an irreversible reduction peak at E_p = −2.169 V, which is likely related to the electrochemical transformation of the nitronyl nitroxide moieties. Crystallization from an acetone/benzene solution yielded crystals of [Ag–(IPr)₂][Ag–(NN)₂]·2H₂O solvate, in which the diradical anion [Ag–(NN)₂]⁻ is bound to two water molecules by hydrogen bonds. These hydrogen bonds stabilize a planar conformation of the [Ag–(NN)₂]⁻ anion, in which both NN fragments lie in the same plane and, according to DFT calculations, are linked by fairly strong antiferromagnetic interaction. DFT calculations also predict the dissociation of the complex with water in toluene solution and a conformational change leading to the appearance of about 90° between NN fragments and a significant decrease in exchange interaction. Full article

High-order Poincaré sphere (HOPS) beams have attracted tremendous interest due to their complex polarization and phase characteristics. However, manipulating the second harmonics generation (SHG) of HOPS beams is still challenging. Here, we developed a vector-coupled wave model to predict petal-shaped intensity patterns and reveal a linear correlation between petal number and topological order (n = 2 → 4). Moreover, we experimentally investigated the multidimensional regulation of SHG in HOPS beams through tailored phase-matching strategies. By employing three distinct configurations—(i) type-I phase matching, (ii) type-II phase matching, and (iii) orthogonally arranged BBO crystals based on Type-I phase matching—we establish a comprehensive framework for controlling the spatial and polarization properties of SHG in n = 2 HOPS beams. These results advance the manipulation of structured light in nonlinear optics, providing insights for optimizing applications in optical communication and polarization imaging. Full article

Three-dimensional (3D) printing, also known as additive manufacturing (AM), has become increasingly integrated into dentistry because of its high precision, efficiency, and ability to fabricate patient-specific devices. This review comprehensively discusses the historical development of 3D printing and outlines the fundamental principles of the most widely used technologies in dentistry, including stereolithography (SLA), digital light processing (DLP), and liquid crystal display (LCD). These technologies enable the accurate and efficient fabrication of dental models, crowns, bridges, dentures, surgical guides, orthodontic appliances, and tissue engineering scaffolds. Current clinical applications are systematically summarized across major dental disciplines, including prosthodontics, orthodontics, oral and maxillofacial surgery, endodontics, periodontics, and pediatric dentistry. Despite existing challenges, such as limited long-term clinical data for certain materials, high initial equipment costs, and post-processing requirements, 3D printing offers substantial advantages in terms of customization, workflow efficiency, and clinical predictability of the final product. Future developments in advanced biomaterials, artificial intelligence-assisted workflows, bioprinting, and four-dimensional (4D) printing are expected to further expand the role of additive manufacturing in personalized and regenerative dentistry. Full article

In this work, the electronic, structural, and magnetic properties of Ti-, V-, Cr-, Mn-, and Ni-doped AgZnF₃ perovskites are systematically investigated using the Korringa–Kohn–Rostoker method combined with the coherent potential approximation (KKR-CPA) within the generalized gradient approximation (GGA). Transition metal dopants (Ti and V) at a concentration of 5% substituting the Zn site introduce 3d states that cross the Fermi level in the majority-spin channel, resulting in half-metallic behavior. Ferromagnetic stability is predicted for Ti-, V-, Cr-, and Mn-doped AgZnF₃ at a doping concentration of 5%. The TM-doped AgZnF₃ alloys exhibit noticeable variations in exchange splitting between the t₂g and e_g states of the TM-3d orbitals. In Ti-doped AgZnF₃, the calculated spin magnetic moments follow the expected trend based on crystal-field splitting theory. Furthermore, a clear correlation is observed between the nature of the transition metal dopant (Ti, V, Cr, Mn, and Ni) and the total magnetic moment of the system. Full article

The present work set out to examine the antidiabetic capacity of Abelmoschus esculentus (okra) fruit extract through a combined experimental and computational framework. Enzyme inhibition assays were carried out against four metabolic targets, and IC₅₀ values stood at 7.66 ± 0.31 mg/mL for alpha-glucosidase, 5.21 ± 0.18 mg/mL for alpha-amylase, 2.11 ± 0.15 microg/mL for DPP-4, and 9.17 ± 0.54 mg/mL for pancreatic lipase. The extract showed moderate-to-weak activity relative to standard inhibitors acarbose, sitagliptin, and orlistat. Sixteen drug-like phytochemicals obtained from the IMPPAT 2.0 database were docked against the crystal structures of all four tested enzymes (PDB: 8CB1, 5E0F, 2ONC, 1LPB). Alpha-Carotene, Vitamin E, and Spiraeoside emerged as the top-ranked compounds across all targets, with alpha-Carotene recording the strongest binding affinity of −11.1 kcal/mol against pancreatic lipase, which was 4.2 kcal/mol more negative than the positive control orlistat (−6.9 kcal/mol). PLIP-based interaction profiling mapped out hydrogen bonds, hydrophobic contacts, pi-stacking, and salt bridges at the atomic level. Absorption, distribution, metabolism, and excretion (ADME) and toxicity screening of alpha-Carotene returned a favourable pharmacokinetic profile with predicted LD₅₀ of 1510 mg/kg (Class 4) and inactivity across most toxicity endpoints. A 100 ns molecular dynamics simulation of the pancreatic lipase-alpha–Carotene complex, alongside the orlistat control, showed stable root mean square deviation (RMSD) (0.15–0.22 nm), a consistent Rg (~1.97 nm), and sustained hydrogen bonding throughout the trajectory. Free-energy landscape analysis revealed a well-defined single energy basin for alpha-Carotene, suggesting a thermodynamically stable binding conformation. These findings lay the molecular basis for using okra phytochemicals as adjunctive agents in diabetes management, though in vivo validation remains necessary. Full article