Fluid Phase Equilibria最新文献

In this work, the Binding-MSA (BiMSA) theory is implemented in an equation of state for the first time. The proposed model, BiMSA-electrolyte polar perturbed chain statistical associating fluid Theory (BiMSA-ePPC-SAFT), is applied to aqueous and mixed solvent electrolyte systems (water + methanol and water + ethanol) to investigate the impact of ion pairs. In a first step, a comparison is made between the Bjerrum and Wertheim theories for the calculation of the ion-ion association strength. The results obtained show that the Bjerrum theory is more successful in describing the association of ions especially in mixed solvent systems. In a second step, different types of relative static permittivity (RSP) models are implemented and compared. The obtained results reveal that using the Bjerrum theory with a volume-dependent RSP yields an ion-ion association strength that strongly changes with salinity. The models are further analyzed focusing on the relative importance of the various types of association (ion-solvent, solvent-solvent, solvent-cosolvent and cosolvent-cosolvent). It was observed that in an aqueous solution, ion-solvent and solvent-solvent association bonds are stronger and more important than those of ion pairing. However, for the mixed solvent systems, in high alcohol concentration, ion pairs exhibit the strongest bond.

Large overestimation has been reported while predicting the thermal conductivity of hydrocarbons using an all-atom force field model in molecular dynamics (MD) simulations. Although it has been guessed as resulting from the high-frequency vibration of the hydrogen atoms and hydrogen constraints method is suggested to be employed to reduce the deviation, how hydrogen constraints affect the heat conduction and local structure of hydrocarbons in MD simulation is still not fully understood. In this work, the effect of hydrogen constraints on the prediction of thermal conductivity of n-decane in MD simulations with the all-atom force field is studied. The results show that the deviation of the thermal conductivity of n-decane can be narrowed down by 72.48 % in simulations if the hydrogen constraints with a SHAKE algorithm is employed. The analysis of heat flux decomposition indicates that employing hydrogen constraints can reduce the contribution of transport term and non-bonded interactions to the heat flux, which in turn can help improve the accuracy while predicting the thermal conductivity in MD simulations. Furthermore, results of the vibrational density of states show that hydrogen constraints can dismiss the high-frequency vibration mode of molecules, thus effectively reducing the overestimation of thermal conductivity of hydrocarbon systems in MD simulations. The findings of this work sheds light on the molecular mechanism of heat transfer in hydrocarbon systems.

The phase behavior of a carbon dioxide (CO₂)/toluene (Tol)/poly(ethylene glycol) (PEG) ternary system was investigated in this study to consider the effect of the polymer species on the phase diagram. Measurements were performed using a synthetic method combined with laser displacement and turbidity measurements. Bubble points (vapor–liquid phase separation) were determined from changes in the piston displacement and cloud points (liquid–liquid (LL) phase separation) were determined from changes in the turbidity. The phase boundaries of the CO₂ mass fractions ranging from 0.113 to 0.496 were measured by varying the Tol/PEG mass ratio. The homogeneous phase area decreased when the mass ratio of PEG to Tol increased and/or the temperature decreased. These changes in the LL phase-separation behavior were explained by referring to the free volume fraction and solubility parameter estimated using the Sanchez–Lacombe equation of state. The free volume integral fraction could explain the phase diagram, but not the solubility parameter; the effect of polymer species on the Px phase diagram of the ternary system was explained by considering specific interactions between dissimilar components. These results could promote a comprehensive understanding of the phase diagram of CO₂/organic solvent/polymer systems and aid the prediction of phase behavior.

In this work, the capability of the Cubic Two State (CTS) equation of state (EoS) has been evaluated using the solubility of carbon dioxide (CO₂), hydrogen sulfide (H₂S), and their mixture in ionic liquids (ILs). The imidazolium-based ILs with [BF₄], [PF₆], and [Tf₂N] anions have been studied. The self-association between IL molecules, CO₂, and H₂S molecules has been considered to optimize the pure model parameters. In addition to self-association between similar molecules, the cross-association between CO₂-IL and H₂S-IL in the binary mixtures has been considered. The results show that the CTS EoS can predict (k_ij=0.0) the solubility of H₂S and CO₂ in ILs ranging from 1 to 1000 bar satisfactory. The average ARD value for binary CO₂-IL and H₂S-IL systems has been obtained 20.3 % and 9.02, respectively. The CTS model has been used to predict the phase behavior of ternary systems containing CO₂H₂S-[C₄mim][PF₆], CO₂H₂S-[C₈mim][PF₆], and CO₂H₂S-[C₈mim][Tf₂N] at various temperatures. Finally, the CTS results have been compared to soft-SAFT and PC-SAFT EoSs. The results show that simple association contribution and the cubic term of the CTS EoS can model the molecular interactions between gases and ILs satisfactory. The CTS model can be considered as a robust and efficient thermodynamic model for the prediction of separation of CO₂ and H₂S using ILs.

Understanding gas hydrate behaviour under confinement is crucial to the development of strategies to efficiently extract methane from hydrate reservoirs. Thus, we have performed molecular dynamics simulations of methane hydrate dissociation inside a hydrophilic silica slit nanopore (representing the pores present in naturally occurring hydrate reservoirs) in the canonical ensemble at 290, 300, 305, and 310 K. Methane hydrate dissociates at lower temperatures under confinement than in bulk. Hydrate dissociation under confinement proceeds in a shrinking core manner showing an increased dissociation rate in the confined system compared to the bulk system where the dissociation is layer-by-layer only. Under confinement, the observed Arrhenius-type behaviour of the methane hydrate dissociation rate (in the initial 5 ns) with temperature leads to a value of the activation energy of dissociation (i.e., 46.885 kJ/mol) to be twice the hydrogen bond energy. In contrast to the confined system, the activation energy of dissociation in the bulk system is higher (i.e., 56.928 kJ/mol). The hydrophobic methane nanobubble formed after the dissociation tends to adhere to the hydrophilic silica substrate and there is an ordered bound water layer on the hydrophilic silica surface underneath the methane nanobubble, with the water molecules in this bound water layer region ordered in a square lattice arrangement unlike the random orientation of water molecules in the bound water layer at other regions on the hydroxylated silica surface. This ordered arrangement of the bound water molecules underneath the nanobubble maximizes the hydrogen bonding between bound water molecules and the surface hydroxyl groups (i.e., one water molecule is associated with a pair of hydroxyl groups). Our study, thus brings this detailed molecular-level structural insight into the complex interactions that exist among methane, water, and the hydrophilic silica surface under confinement for the first-time, to the best of our knowledge.

Viscosity, the measure of a fluid's resistance to deformation, is a critical parameter in many industries. Being able to accurately predict viscosity is essential for the successful design and optimization of technological processes. In this research, regression models were created to predict the viscosity of deep eutectic solvents (DESs). Machine learning models were trained using a data set of 3440 data points for two component DESs. Different algorithms, such as Multiple Linear Regression, Random Forest, CatBoost, and Transformer CNF, were employed alongside a variety of structural representations like fingerprints, σ-profiles, and molecular descriptors. The effectiveness of the models was assessed for interpolation tasks within the training data and extrapolation outside of it. The results indicate that a rigorous splitting of the dataset into subsets is necessary to accurately evaluate the performance of the models. Two new choline chloride-based DESs were prepared and their viscosities were measured to evaluate the predictive capabilities of the models. The CatBoost algorithm with CDK molecular descriptors was chosen as the recommended model. The average absolute relative deviations (AARD) of this model exhibited fluctuations during 5-fold cross-validation, ranging from 10.8 % when interpolating within the dataset to 88 % when extrapolating to new mixture components. The open access model was presented in this study (http://chem-predictor.isc-ras.ru/ionic/des/).

Molten salt reactors (MSRs) offer significant advancements in nuclear reactor safety and efficiency by operating at higher temperatures and lower pressures compared to traditional reactors. A critical aspect of MSR operation involves understanding the solubility of fission byproducts, particularly noble gases, in the molten salts used. This study employs molecular dynamics (MD) simulations to compute Henry’s law constants and enthalpies of solvation for argon and xenon in molten sodium chloride (NaCl) and potassium chloride (KCl). We developed a new pairwise potential for the noble gas and salt interactions based on first principles calculations. We then used this potential to calculate Henry’s law constants of the two gases in the molten salts, which were modeled using both a rigid ion model (RIM) and a polarizable ion model (PIM). The solubility calculations, performed using the Widom insertion method, show qualitative agreement with limited experimental data, highlighting the temperature dependence and greater solubility of both gases in KCl compared to NaCl. Additionally, free volume analysis elucidated the role of available space within the molten salts in governing solubility trends. Our findings suggest that PIM trajectories provide more reliable predictions for noble gas solubility than RIM due to their accurate density representation. These results enhance understanding of gas solubility in MSR environments, and the methods can be readily extended to other systems.

Present work details the determination of three phase hydrate equilibrium data (H-L-V) using temperature search method for the binary CO₂/CH₄ gas mixture (50:50 molar ratio) in presence of 1,3 dioxolane (DIOX). DIOX concentration used for phase equilibrium determination were 1,3 and 5.56 mol% respectively. In the presence of DIOX, it was observed that phase equilibrium curve was shifted right with respect to the curve using same gas mixture with no additive (pure water). This indicates that the presence of DIOX moderates the hydrate formation equilibrium conditions. Also, as DIOX concentration increases from 1 mol% to 5.56 mol%, a decrement in phase equilibrium pressure at same temperatures was observed, confirming the potential of DIOX as an effective thermodynamic promoter. Enthalpy of hydrate dissociation was calculated for CO₂/CH₄ gas mixture in presence of DIOX using Clausius- Clapeyron plot and it was found to be 90.81±6.55 KJ/mol which confirms the sII structure of CO₂-CH₄-DIOX mixed hydrate. Besides providing the phase equilibrium data of formed hydrates with CO₂/CH₄ gas mixture using different concentration of DIOX, the present study will aid in determining suitable experimental conditions for examining kinetics and performing separation studies of CO₂/CH₄ gas mixture through hydrate formation.

The interest in understanding reservoir fluids' phase behavior is to increase hydrocarbon production without any flow assurance issues. Due to its opacity, the evident complexity of determining phase equilibrium data revolves around the thermodynamic modeling of model systems. The article presents experimental phase equilibrium data and thermodynamic modeling for the CO₂ + decane + hexadecane ternary system at 283.15, 298.15, and 323.15 K and pressures up to 20 MPa. The transitions observed during this study were liquid-liquid (LL), vapor-liquid (VL), and vapor-liquid-liquid (VLL). The Peng-Robinson equation of state was used to model this ternary system for various compositions. The temperature-dependent binary interaction parameters (k_ij) for the CO₂ + n-alkane mixtures were adjusted to the experimental data. Additionally, a binary interaction parameter for the n-C₁₆H₃₄/n-C₁₀H₂₂ pair, independent of temperature, was obtained through the critical volume of the components. The results reveal complex behaviors as the mixture's composition of hexadecane progressively increases. Adding this longer-chain linear hydrocarbon influences the phase behavior, leading to the emergence of liquid-liquid transitions and barotropic inversion in the system. This study contributes valuable data on model systems representing crude oil, highlighting complex behaviors in ternary systems with high carbon dioxide content.