Search Results (963)

Nucleation and growth during the crystallization process are crucial steps that determine the crystal structure, size, morphology, and purity. A thorough understanding of these mechanisms is essential for producing crystalline products with consistent properties. This study investigates the solubility of tacrolimus (FK506) in an ethanol–water system (1:1, v/v) and examines its crystallization kinetics using batch crystallization experiments. Initially, the solubility of FK506 was measured, and classical nucleation theory was employed to analyze the induction period to determine interfacial free energy ($\gamma$) and other nucleation parameters, including the critical nucleus radius ($r^{*}$), critical free energy ($∆G^{*}$), and the molecular count of the critical nucleus ($i^{*}$). Crystallization kinetics under seeded conditions were also measured, and the parameters of the kinetic model were analyzed to understand the effects of process states such as temperature on the crystallization process. The results suggested that increasing temperature and supersaturation promotes nucleation. The surface entropy factor ($f$) indicates that the tacrolimus crystal growth mechanism is a two-dimensional nucleation growth. The growth process follows the particle size-independent growth law proposed by McCabe. The estimated kinetic parameters reveal the effects of supersaturation, temperature, and suspension density on the nucleation and growth rates. Full article

This study investigates the modeling and experimental validation of cell morphology in microcellular-foamed polycaprolactone (PCL) using supercritical carbon dioxide (scCO₂) as the blowing agent. The microcellular foaming process (MCP) was conducted using a solid-state batch foaming process, where PCL was saturated with scCO₂ at 6 to 9 MPa and 313 K, followed by depressurization at a rate of −0.3 and −1 MPa/s. This study utilized the Sanchez–Lacombe equation of state and the Peng–Robinson–Stryjek–Vera equation of state to model the solubility and density of the PCL-CO₂ mixture. Classical nucleation theory was modified and combined with numerical analysis to predict cell density, incorporating factors such as gas absorption kinetics, the role of scCO₂ in promoting nucleation, and the impact of depressurization rate and saturation pressure on cell growth. The validity of the model was confirmed by comparing the theoretical predictions with experimental and reference data, with the cell density determined through field-emission scanning electron microscopy analysis of foamed PCL samples. This study proposes a method for predicting cell density that can be applied to various polymers, with the potential for wide-ranging applications in biomaterials and industrial settings. This research also introduces a Python-based numerical analysis tool that allows for easy calculation of solubility and cell density based on the material properties of polymers and penetrant gases, offering a practical solution for optimizing MCP conditions in different contexts. Full article

A natural extract, i.e., urushiol, was employed to effectively cross-link and modify commercial wet-cured polyurethane acrylic resin. Comprehensive characterization of the paint film was performed using techniques such as FTIR, SEM, and TGA. The results indicated that the incorporation of urushiol significantly increased the cross-linking density of the resin, which in turn enhanced the film-forming properties, mechanical strength, and thermal stability of the paint film. Additionally, the study discovered that under isothermal conditions, the dynamic moduli (G′ and G″) of the paint film are related to the gel point frequency by a power law, aligning with the predictions of percolation theory. The application of the autocatalytic model has provided a novel approach to studying non-isothermal kinetic reactions, offering valuable insights for process optimization and further development of urushiol-based polyurethane. Full article

Polychlorinated naphthalenes (PCNs) are a new type of persistent organic pollutant (POP) characterized by persistence, bioaccumulation, dioxin-like toxicity, and long-range atmospheric transport. Focusing on one type of PCN, monochlorinated naphthalenes (CN-1, CN-2), this study aimed to examine their photodegradation in the environment. In this work, CN-1 and CN-2 were employed as the model pollutants to investigate their photodegradation process under UV-C irradiation. Factors like the pH, initial concentrations of CN-1, and inorganic anions were investigated. Next, the roles of hydroxyl radicals (^•OH), superoxide anion radicals (O₂^•−), and singlet oxygen (¹O₂) in the photodegradation process were discussed and proposed via theory computation. The results show that the photodegradation of CN-1 and CN-2 follows pseudo-first-order kinetics. Acidic conditions promote the photodegradation of CN-1, while the effects of pH on the photodegradation of CN-2 are not remarkable. Cl⁻, NO₃⁻, and SO₃²⁻ accelerate the photodegradation of CN-1, whereas the effect of SO₄²⁻ and CO₃²⁻ is not significant. Additionally, the contributions of ^•OH and O₂^•− to the photodegradation of CN-1 are 20.47% and 38.80%, while, for CN-2, the contribution is 16.40% and 16.80%, respectively. Moreover, the contribution of ¹O₂ is 15.7%. Based on DFT calculations, C4 and C6 of the CN-1 benzene ring are prioritized attack sites for ^•OH, while C2 and C9 of CN-2 are prioritized attack sites. Full article

Biochar prepared from crop straw is an economical method for adsorbing bromocresol green (BCG) from textile industrial wastewater. However, there is limited research on the adsorption mechanism of biochar for the removal of BCG. This study utilized cucumber straw as raw material to prepare biochar with good adsorption potential and characterized its physicochemical properties. Through adsorption experiments, the effects of solution pH, biochar dosage, and initial dye concentration on adsorption performance were examined. The adsorption mechanism of cucumber straw biochar (CBC) for BCG was elucidated at the molecular level using adsorption kinetics, adsorption isotherm models, and density functional theory (DFT) calculations. Results show that the specific surface area of the CBC is 101.58 m²/g, and it has a high degree of carbonization, similar to the structure of graphite crystals. The presence of aromatic rings, –OH groups, and –COOH groups in CBC provides abundant adsorption sites for BCG. The adsorption process of CBC for BCG is influenced by both physical and chemical adsorption, and can be described by the Langmuir isotherm model, indicating a monolayer adsorption process. The theoretical maximum monolayer adsorption capacity (q_m) of BCG at 298 K was calculated to be 99.18 mg/g. DFT calculations reveal interactions between BCG and CBC involving electrostatic interactions, van der Waals forces, halogen–π interactions, π–π interactions, and hydrogen bonds. Additionally, the interaction of hydrogen bonds between BCG and the –COOH group of biochar is stronger than that between BCG and the –OH group. These findings provide valuable insights into the preparation and application of efficient organic dye adsorbents. Full article

This research paper presents an experimental, theoretical, and numerical study of the thermomechanical behavior of single-crystal and polycrystal copper under uniaxial stress compression loading at varying rates of deformation. The thermomechanical theory is based on a thermodynamically consistent framework for single-crystal face-centered cubic metals, and assumes that all plastic power is partitioned between stored energy due to dislocation structure evolution (configurational) and thermal (kinetic vibrational) energy. An expression for the Taylor–Quinney factor is proposed, which is a simple function of effective temperature and is allowed by second-law restrictions. This single-crystal model is used for the study of single- and polycrystal copper. New polycrystal thermomechanical experimental results are presented at varying strain rates. The temperature evolution on the surface of the polycrystal samples is measured using mounted thermocouples. Thermomechanical numerical single- and polycrystal simulations were performed for all experimental conditions ranging between ${10}^{-3}$ and 5 × ${10}^3$ ${\mathrm{s}}^{-1}$. A Taylor homogenization model is used to represent polycrystal behavior. The numerical simulations of all conditions compare reasonable well with experimental results for both stress and temperature evolution. Given our lack of understanding of the mechanisms responsible for the coupling of dislocation glide and atomic vibration, this implies that the proposed theory is a reasonably accurate approximation of the single-crystal thermomechanics. Full article

This study presents a self-consistent one-temperature approach for modeling shock waves in single-component methane. The rigorous mathematical model takes into account the complex structure of CH₄ molecules with multiple vibrational modes and incorporates exact kinetic theory-based transport coefficients, including bulk viscosity. The effects of the bulk viscosity on gas-dynamic variables and transport terms are investigated in detail under varying degree of gas rarefaction. It is demonstrated that neglecting bulk viscosity significantly alters the shock front width and peak values of normal stress and heat flux, with the effect being more evident in denser gases. The study also evaluates limitations in the use of a constant specific heat ratio, revealing that this approach fails to accurately predict post-shock parameters in polyatomic gases, even at moderate Mach numbers. To enhance computational efficiency, a simplified approach based on a reduced vibrational spectrum is assessed. The results indicate that considering only the ground state leads to substantial errors in the fluid-dynamic variables across the shock front. Another approach explored involves the application of machine learning techniques to calculate vibrational energy and specific heat. Among the methods tested, the Feedforward Neural Network (FNN) proves to be the most effective, offering significant acceleration in calculations and providing one of the lowest errors. When integrated into the fluid-dynamic solver, the FNN approach yields nearly a three-fold increase in speed in numerical simulations of the shock wave structure. Full article

Ceiba aesculifolia is an important species in Mexico that generates significant amounts of biomass waste during its exploitation, which can be utilized to produce energy. This study presents the characterization of this waste based on chemical (proximal and elemental) and thermal analyses (TGA-DTG) at different heating rates (β = 10–30 °C/min (283–303 K/min)) in the presence of nitrogen and in a temperature range of 25–900 °C. Kinetic parameters were calculated and analyzed as well. Activation energy (Ea) and the pre-exponential factor (A) were determined using the Friedman (132.03 kJ/mol, 8.11E + 10 s ⁻¹), FWO (121.65 kJ/mol, 4.30E + 09), KAS (118.14 kJ/mol, 2.41E + 09), and Kissinger (155.85 kJ/mol, 3.47E + 11) kinetic methods. Variation in the reaction order, n (0.3937–0.6141), was obtained by Avrami’s theory. We also calculated the thermodynamic parameters (ΔH, ΔG, ΔS) for each kinetic method applied. The results for Ea, A, n, ΔH, ΔG, and ΔS show that this biomass waste is apt for use in pyrolysis. Moreover, the moisture (<10%), ash (<2%), volatile material (>80%), and HHV (>19%) contents of C. aesculifolia allowed us to predict acceptable performance in generating energy and fuels. Finally, infrared spectroscopy analysis (FT-IR) allowed us to identify important functional groups, including one that belongs to the family of the aliphatic hydrocarbons. Full article

The intramolecular H-migration reaction of R^IOR^IIOO· radicals constitute a key class of reactions in the low-temperature combustion mechanism of ethers. Despite this, there is a dearth of direct computations regarding the potential energy surface and rate constants specific to ethers, especially when considering large molecular systems and intricate branched-chain structures. Furthermore, combustion kinetic models for large molecular ethers generally utilize rate constants derived from those of structurally similar alcohols or alkane fuels. Consequently, chemical kinetic studies involve the calculation of energy barriers and rate rules for the intramolecular H-migration reaction class of R^IOR^IIOO· radicals, which are systematically conducted using the isodesmic reaction method (IRM). The geometries of the species participating in these reactions are optimized, and frequency calculations are executed using the M06–X method in tandem with the 6–31+G(d,p) basis set by the Gaussian 16 program. Moreover, the M06–2X/6–31+G(d,p) method acts as the low-level ab initio method, while the CBS–QB3 method is utilized as the high-level ab initio method for calculating single-point energies. Rate constants at the high-pressure-limit are computed based on the reaction class transition state theory (RC-TST) by ChemRate program, incorporating asymmetric Eckart tunneling corrections for intramolecular H-migration reactions across a temperature range of 500 to 2000 K. It was found that the isodesmic reaction method gives accurate energy barriers and rate constants, and the rate constants of the H-migration reaction for R^IOR^IIOO· radicals diverge from those of comparable reactions in alkanes and alcohol fuels. There are significant disparities in energy barriers and rate constants across the entire reaction classes of the H-migration reaction for R^IOR^IIOO· radicals, necessitating the subdivision of the H-migration reaction into subclasses. Rate rules are established by averaging the rate constants of representative reactions for each subclass, which is pivotal for the advancement of accurate low-temperature combustion reaction mechanisms for ethers. Full article

Anthocyanins, typical polyphenol compounds in grape skin, have attracted increasing interest due to their health-promoting properties. In this body of work, five representative anthocyanins (Cy-3-O-glc, Dp-3-O-glc, Pn-3-O-glc, Mv-3-O-glc, and Pt-3-O-glc) were studied using the density functional theory (DFT) to elucidate structure–radical scavenging activity in the relationship and the reaction path underlying the radical-trapping process. Based on thermodynamic parameters involved in HAT, SET-PT, and SPLET mechanisms, along with the structural attributes, it was found that the C4′ hydroxyl group mainly contributes to the radical scavenging activities of the investigated compounds. Pt-3-O-glc exhibits a good antioxidant capacity among the five compounds. The preferred radical scavenging mechanisms vary in different phases. For the Pt-3-O-glc compound, the calculations indicate the thermodynamically favoured product is benzodioxole, rather than o-quinone, displaying considerably reduced energy in double HAT mechanisms. Additionally, the thermodynamic and kinetic calculations indicate that the reaction of ^•OH into the 4′-OH site of Pt-3-O-glc has a lower energy barrier (7.6 kcal/mol), a higher rate constant (5.72 × 10⁹ M⁻¹ s⁻¹), and exhibits potent ^•OH radical scavenging properties. Molecular docking results have shown the strong affinity of the studied anthocyanins with the pro-oxidant enzyme xanthine oxidase, displaying their significant role in inhibiting ROS formation. Full article

To investigate the influence of varied mechanical parameters of coal mass on rock burst occurrence during deep roadway tunneling, the surrounding coal and rock mass of a deep roadway were taken as the research objects. A geometric model of roadway tunneling was developed using 3DEC numerical simulation software, and the failure characteristics of the coal mass in the roadway side were analyzed based on the rock burst mechanism and stress difference gradient theory for deep mining. The risk of rock burst during roadway tunneling was quantitatively assessed using the change rate of the stress difference gradient (D_gc), thereby elucidating the burst failure patterns of the deep roadway under the influence of varied mechanical parameters. The findings indicate that the coal mass in the roadway side zone is more prone to burst failure due to stress disturbances during deep excavation compared to the coal and rock mass in the roof and floor zones, and that the released kinetic energy and the risk of burst failure are positively correlated with the magnitude of the ground stress. The variation of the mechanical properties of coal mass has a significant effect on the rock burst risk during roadway tunneling. The variation of both internal friction angle and cohesion significantly affects rock burst, with cohesion exerting a greater influence. Conversely, the elastic modulus does not significantly impact the risk. The tendency of bursting in the coal mass is positively correlated with the coefficient of variation (COV) in cohesion and negatively correlated with the COV in internal friction angle. These research findings offer valuable insights for the quantitative assessment of rock burst risk during roadway tunneling. Full article

Ruthenium(II) polypyridyl complexes are being tested as potential anticancer agents in different therapies, which include conventional chemotherapy and light-activated approaches. A mechanistic study on a recently synthesized dual-action Ru(II) complex [Ru(bpy)₂(sora)Cl]⁺ is described here. It is characterized by two mono-dentate leaving ligands, namely, chloride and sorafenib ligands, which make it possible to form a di-aquo complex able to bind DNA. At the same time, while the released sorafenib can induce ferroptosis, the complex is also able to act as a photosensitizer according to type II photodynamic therapy processes, thus generating one of the most harmful cytotoxic species, ¹O₂. In order to clarify the mechanism of action of the drug, computational strategies based on density functional theory are exploited. The photophysical properties of the complex, which include the absorption spectrum, the kinetics of ISC, and the character of all the excited states potentially involved in ¹O₂ generation, as well as the pathway providing the di-aquo complex, are fully explored. Interestingly, the outcomes show that light is needed to form the mono–aquo complex, after releasing both chloride and sorafenib ligands, while the second solvent molecule enters the coordination sphere of the metal once the system has come back to the ground-state potential energy surface. In order to simulate the interaction with canonical DNA, the di-aquo complex interaction with a guanine nucleobase as a model has also been studied. The whole study aims to elucidate the intricate details of the photodissociation process, which could help with designing tailored metal complexes as potential anticancer agents. Full article

Models of chemical kinetic processes, comprising systems of stiff ordinary differential equations (ODEs), are essential for modeling important chemical reactions relevant to drinking water chemistry, such as disinfectant decay and disinfection byproduct formation. However, the accuracy of these models can be inhibited by (1) the challenge of fully describing the chemical reaction system, and (2) additional chemical reactions occurring in actual environmental settings that were not accounted for in the laboratory conditions used to develop and calibrate the models. This study proposes the use of a Physics-Informed Neural Network framework, utilizing the eXtreme Theory of Functional Connections (X-TFC) technique to create a hybrid chemical- and data-driven model that incorporates data and the underlying system of ODEs into the trained model in order to increase the accuracy of the predicted chemical concentrations. Full article

A sustainable low-cost activated carbon substitute was produced based on pretreated lignocellulosic biomass, especially spruce sawdust. A harmful liquid waste, desalination brine, was used for the treatment of a solid wood industry waste, spruce sawdust. This approach is in the circular economy theory and aims at the decarbonization of the economy. Pretreated sawdust was tested as an adsorbent appropriate for the removal of a commonly used pollutant, methylene blue, from industrial wastewater. The adsorption capacity of the pretreated material was found to have increased four times compared to the untreated one in the case that the Freundlich equation was fitted to the isotherms’ data, i.e., the one with the best fit to the isotherm’s experimental data of the three isotherm models used herein. The treatment experimental conditions with desalination brine that gave maximum adsorption capacity correspond to a 1.97 combined severity factor in logarithmic form value. Moreover, a kinetic experiment was carried out with regard to the methylene blue adsorption process. The desalination brine-pretreated sawdust adsorption capacity increased approximately two times compared to the untreated one, in the case when the second-order kinetic equation was used, which had the best fit of the kinetic data of the three kinetic models used herein. In this case, the pretreatment experimental conditions that gave maximum adsorption capacity correspond to −1.049 combined severity factor in logarithmic form. Industrial scale applications can be based on the kinetic data findings, i.e., spruce sawdust optimal pretreatment conditions at 200 °C, for 25 min, with brine solution containing 98.12 g L⁻¹ NaCl, as they are related to a much shorter adsorption period compared to the isotherm data. Full article

The Boltzmann equation with multiple-relaxation-time (MRT) collision operators has been widely employed in kinetic theory to describe the behavior of gases and liquids at the macro-level. Given the successful development of deep learning and the availability of data analytic tools, it is a feasible idea to try to solve the Boltzmann-MRT equation using a neural network-based method. Based on the canonical polyadic decomposition, a new physics-informed neural network describing the Boltzmann-MRT equation, named the network for MRT collision (NMRT), is proposed in this paper for solving the Boltzmann-MRT equation. The method of tensor decomposition in the Boltzmann-MRT equation is utilized to combine the collision matrix with discrete distribution functions within the moment space. Multiscale modeling is adopted to accelerate the convergence of high frequencies for the equations. The micro–macro decomposition method is applied to improve learning efficiency. The problem-dependent loss function is proposed to balance the weight of the function for different conditions at different velocities. These strategies will greatly improve the accuracy of the network. The numerical experiments are tested, including the advection–diffusion problem and the wave propagation problem. The results of the numerical simulation show that the network-based method can obtain a measure of accuracy at $O\left({10}^{-3}\right)$. Full article