Developing intermolecular‐potential models for use with the SAFT ‐ VR M ie equation of state

Atomic-Scale Insights into the Phase Behavior of Carbon Dioxide and Water from 313 to 573 K and 8 to 30 MPa

We performed molecular dynamics (MD) simulations of CO2 + H2O systems by employing widely used force fields (EPM2, TraPPE, and PPL models for CO2; SPC/E and TIP4P/2005 models for H2O). The phase behavior observed in our MD simulations is consistent with the coexistence lines obtained from previous experiments and SAFT-based theoretical models for the equations of state. Our structural analysis reveals a pronounced correlation between phase transitions and the structural orderliness. Specifically, the coordination number of Ow (oxygen in H2O) around other Ow significantly correlates with phase changes. In contrast, coordination numbers pertaining to the CO2 molecules show less sensitivity to the thermodynamic state of the system. Furthermore, our data indicate that a predominant number of H2O molecules exist as monomers without forming hydrogen bonds, particularly in a CO2-rich mixture, signaling a breakdown in the hydrogen bond network's orderliness, as evidenced by a marked decrease in tetrahedrality. These insights are crucial for a deeper atomic-level understanding of phase behaviors, contributing to the well-grounded design of CO2 injection under high-pressure and high-temperature conditions, where an atomic-scale perspective of the phase behavior is still lacking.

Prediction of water anomalous properties by introducing the two-state theory in SAFT

Water is one of the most abundant substances on earth, but it is still not entirely understood. It shows unusual behavior, and its properties present characteristic extrema unlike any other fluid. This unusual behavior has been linked to the two-state theory of water, which proposes that water forms different clusters, one with a high density and one with a low density, which may even form two distinct phases at low temperatures. Models incorporating the two-state theory manage to capture the unusual extrema of water, unlike traditional equations of state, which fail. In this work, we have derived the framework to incorporate the two-state theory of water into the Statistical-Associating-Fluid-Theory (SAFT). More specifically, we have assumed that water is an ideal solution of high density water molecules and low density water molecules that are in chemical equilibrium. Using this assumption, we have generalized the association term SAFT to allow for the simultaneous existence of the two water types, which have the same physical parameters but different association properties. We have incorporated the newly derived association term in the context of the Perturbed Chain-SAFT (PC-SAFT). The new model is referred to as PC-SAFT-Two-State (PC-SAFT-TS). Using PC-SAFT-TS, we have succeeded in predicting the characteristic extrema of water, such as its density and speed of sound maximum, etc., without loss of accuracy compared to the original PC-SAFT. This new framework is readily extended to mixtures, and PC-SAFT-TS manages to capture the solubility minimum of hydrocarbons in water in a straightforward manner.

Mixed Solvent Electrolyte Solutions: A Review and Calculations with the eSAFT-VR Mie Equation of State

In this work, mixed-solvent mean ionic activity coefficients (MIAC), vapor-liquid equilibrium (VLE), and liquid-liquid equilibrium (LLE) of electrolyte solutions have been addressed. An extended literature review of existing electrolyte activity coefficient models (eGE) and electrolyte equations of state (eEoS) for modeling mixed solvent electrolyte systems is first presented, focusing on the details of the models in terms of physical and electrolyte terms, relative static permittivity, and parameterization. The analysis of this literature reveals that the property predictions can be ranked, from the easiest to the most difficult, in the following order: VLE, MIAC, and LLE. We have then used our previously developed eSAFT-VR Mie model to predict MIAC, VLE, and LLE in mixed solvents without fitting any new adjustable parameters. The model was parameterized on MIAC of aqueous electrolyte solutions and successfully extended to nonaqueous, single solvent electrolyte solutions without any new adjustable parameters by using a salt-dependent expression for the relative static permittivity. Our approach yields excellent results for MIAC and VLE of mixed solvent electrolyte solutions, while being fully predictive. LLE is significantly more challenging, and an accurate model for the salt-free solution is crucial for accurate calculations. When the compositions of the two phases in the binary salt-free system are accurately captured, then the electrolyte extension of our model shows a lot of potential and is currently among the best eEoS for LLE prediction in the literature.

Revised Enskog theory for Mie fluids: Prediction of diffusion coefficients, thermal diffusion coefficients, viscosities, and thermal conductivities

Since the 1920s, the Enskog solutions to the Boltzmann equation have provided a route to predicting the transport properties of dilute gas mixtures. At higher densities, predictions have been limited to gases of hard spheres. In this work, we present a revised Enskog theory for multicomponent mixtures of Mie fluids, where the Barker-Henderson perturbation theory is used to calculate the radial distribution function at contact. With parameters of the Mie-potentials regressed to equilibrium properties, the theory is fully predictive for transport properties. The presented framework offers a link between the Mie potential and transport properties at elevated densities, giving accurate predictions for real fluids. For mixtures of noble gases, diffusion coefficients from experiments are reproduced within ±4%. For hydrogen, the predicted self-diffusion coefficient is within 10% of experimental data up to 200 MPa and at temperatures above 171 K. Binary diffusion coefficients of the CO2/CH4 mixture from simulations are reproduced within 20% at pressures up to 14.7 MPa. Except for xenon in the vicinity of the critical point, the thermal conductivity of noble gases and their mixtures is reproduced within 10% of the experimental data. For other molecules than noble gases, the temperature dependence of the thermal conductivity is under-predicted, while the density dependence appears to be correctly predicted. Predictions of the viscosity are within ±10% of the experimental data for methane, nitrogen, and argon up to 300 bar, for temperatures ranging from 233 to 523 K. At pressures up to 500 bar and temperatures from 200 to 800 K, the predictions are within ±15% of the most accurate correlation for the viscosity of air. Comparing the theory to an extensive set of measurements of thermal diffusion ratios, we find that 49% of the model predictions are within ±20% of the reported measurements. The predicted thermal diffusion factor differs by less than 15% from the simulation results of Lennard-Jones mixtures, even at densities well exceeding the critical density.

Multipolar SAFT-VR Mie Equation of State: Predictions of Phase Equilibria in Refrigerant Systems with No Binary Interaction Parameter

An extension of the SAFT-VR Mie equation of state is proposed to predict the properties of multipolar fluids. The new model, referred to as multipolar M-SAFT-VR Mie, incorporates the general multipolar term developed by Gubbins and co-workers, which accounts for dipole-dipole, quadrupole-quadrupole, and dipole-quadrupole interactions. A modification of the third order terms in the perturbation theory results in an accurate description of the simulation data for multipolar Lennard-Jones fluids. Both the M-SAFT-VR Mie and polar soft-SAFT models are extended to account for polarizability, and a good agreement is obtained with molecular simulation data. The M-SAFT-VR Mie model is applied to refrigerant systems, and it is found that including both dipole and quadrupole moments in molecular models leads to more accurate results than using only a dipole moment. The new model provides excellent predictions of the vapor-liquid equilibria of zeotropic and azeotropic refrigerant mixtures without the need for binary interaction parameters, making it a valuable tool for formulating low-GWP working fluids.

Deriving force fields with a multiscale approach:from ab initio calculations to molecular-based equations of state

Using theoretical and computational tools for predicting thermophysical properties of fluid systems and the soft matter has always been of interest to the physical, chemical, and engineering sciences. And certainly, the ultimate goal is to be able to compute these macroscopic properties from first principle calculations beginning with the very atomic constitution of matter. In this work, Mie potential parameters were obtained through dimer interaction energy curves derived from ab initio calculations to represent methane and methane-substituted molecules in a spherical 1-site coarse-grained model. Bottom-up-based Mie potential parameters of this work were compared to top-down-based ones from the statistical associating fluid theory (SAFT) models for the calculation of thermodynamic properties and critical point by molecular dynamics simulations and SAFT-VR Mie equation of state. Results demonstrated that bottom-up-based Mie potential parameters when averaging the Mie potential parameters of a representative population of conformers provide values close to the top-down-based ones from SAFT models and predict well properties of tetrahedral molecules. This shows the level of consistency embedded in the SAFT-VR Mie family of models and confers a status of a purely predictive equation of state for SAFT-VR Mie when a reasonable model is considered to represent a molecule of interest.

Ab initio development of generalized Lennard-Jones (Mie) force fields for predictions of thermodynamic properties in advanced molecular-based SAFT equations of state

A methodology for obtaining molecular parameters of a modified statistical associating fluid theory for variable-range interactions of Mie form (SAFT-VR Mie) equation of state (EoS) from ab initio calculations is proposed for non-associative species that can be modeled as single spherical segments. The methodology provides a strategy to map interatomic or intermolecular potentials obtained from ab initio quantum-chemistry calculations to the corresponding Mie potentials that can be used within the SAFT-VR Mie EoS. The inclusion of corrections for quantum and many-body effects allows for an excellent, fully predictive description of the vapor-liquid envelope and other bulk thermodynamic properties of noble gases; this description is of similar or superior quality to that obtained using SAFT-VR Mie with parameters regressed in the traditional way using experimental thermodynamic-property data. The methodology is extended to an anisotropic species, methane, where similar levels of accuracy are obtained. The efficacy of using less-accurate quantum-chemistry methods in this methodology is explored, showing that these methods do not provide satisfactory results, although we note that the description is nevertheless substantially better than those obtained using the conductor-like screening model for describing real solvents (COSMO-RS), the only other fully predictive ab initio method currently available. Overall, the reliance on thermophysical data is completely dispensed with, providing the first extensible, wholly predictive SAFT-type EoSs.

Long-time relaxation dynamics in nematic and smectic liquid crystals of soft repulsive colloidal rods

Understanding the relaxation dynamics of colloidal suspensions is crucial to identifying the elements that influence the mobility of their constituents, assessing their macroscopic response across the relevant time and length scales, and thus disclosing the fundamentals underpinning their exploitation in formulation engineering. In this work, we specifically assess the impact of long-ranged ordering on the relaxation dynamics of suspensions of soft repulsive rodlike particles, which are able to self-organize into nematic and smectic liquid-crystalline phases. Rods are modeled as soft repulsive spherocylinders with a length-to-diameter ratio L^{★}=5, interacting via the truncated and shifted Kihara potential. By performing dynamic Monte Carlo simulations, we analyze the effect of translational and orientational order on the diffusion of the rods along the relevant directions imposed by the morphology of the background phases. To provide a clear picture of the resulting dynamics, we assess its dependence on temperature, which can dramatically determine the response time of the system relaxation and the self-diffusion coefficients of the rods. The computation of the van Hove correlation functions allows us to identify the existence of rods that diffuse significantly faster than the average and whose concentration can be accurately adjusted by a suitable choice of temperature.

Atmospheric Ring-Closure and Dehydration Reactions of 1,4-Hydroxycarbonyls in the Gas Phase: The Impact of Catalysts

1,4-Hydroxycarbonyls can potentially undergo sequential reactions involving cyclization followed by dehydration to form dihydrofurans. As dihydrofurans contain a double bond, they are highly reactive toward atmospheric oxidants such as OH, O₃, and NO₃. In the present study, we use ab initio calculations to examine the impact of various atmospheric catalysts on the energetics and kinetics of the gas-phase cyclization and dehydration reaction steps associated with 4-hydroxybutanal, a prototypical 1,4-hydroxycarbonyl molecule. The cyclization step transforms 4-hydroxybutanal into 2-hydroxytetrahydrofuran, which can subsequently undergo dehydration to form 2,3-dihydrofuran. As the barriers associated with the cyclization and dehydration steps for 4-hydroxybutanal are, respectively, 34.8 and 63.0 kcal/mol in the absence of a catalyst, both reaction steps are inaccessible under atmospheric conditions in the gas phase. However, the presence of a suitable catalyst can significantly reduce the reaction barriers, and we have examined the impact of a single molecule of H₂O, HO₂ radical, HC(O)OH, HNO₃, and H₂SO₄ on these reactions. We find that H₂SO₄ reduces the reaction barriers the greatest, with the barrier for the cyclization step being reduced to -13.1 kcal/mol and that for the dehydration step going down to 9.2 kcal/mol, measured relative to their respective separated starting reactants. Interestingly, our kinetic study shows that HNO₃ gives the fastest rate due to the combined effects of a larger atmospheric concentration and a reduced barrier. Thus, our study suggests that, with acid catalysis, the cyclization reaction step can readily occur for 1,4-hydroxycarbonyls in the gas phase. Because the dehydration step exhibits a significant barrier even with acid catalysis, the 2-hydroxytetrahydrofuran products, once formed, are likely lost through their reaction with OH radicals in the atmosphere. We have investigated the reaction pathways and the rate constant for this bimolecular reaction in the presence of excess molecular oxygen (³O₂), as it would occur under tropospheric conditions, using computational chemistry over the 200-300 K temperature range. We find that the main products from these OH-initiated oxidation reactions are succinaldehyde + HO₂ and 2,3-dihydro-2-furanol + HO₂.

Improving the SAFT-γ Mie equation of state to account for functional group interactions in a structural (s-SAFT-γ Mie) framework: Linear and branched alkanes

The group contribution SAFT-γ Mie EoS is based on the statistical associating fluid theory for fused heteronuclear molecules. While the chain term of the model has been modified to account for the new functional group-specific parameters, it does not impose a bonding order to these functional groups, only considering intergroup interactions in the monomer reference fluid. This leaves the model unable to account for the different physical properties of structural isomers and implicitly introducing modeling bias to species where the molecular structure mimics those used in the parameter regression. In this work, a simple but physically meaningful modification to the chain term in SAFT-γ Mie is proposed that accounts for the number of intergroup bonds, thereby encoding structural information in the model, without introducing an additional regressed parameter. The resulting structural SAFT-γ Mie (s-SAFT-γ Mie) requires reparameterization of the group parameters, which we present for linear and branched alkanes (CH₃, CH₂, CH, and C groups) here. Following an identical parameterization procedure to the original model, validation showed that the modification actually improves prediction accuracy for linear alkanes while addressing the original inability of the framework to distinguish between structural isomers. The good predictive performance seen in this work, for both pure component and mixture properties, lays a good foundation for expansion to other functional groups in future work.

SAFT-γ-Mie Cross-Interaction Parameters from Density Functional Theory-Predicted Multipoles of Molecular Fragments for Carbon Dioxide, Benzene, Alkanes, and Water

Determining unlike-pair interaction parameters, whether for group contribution equation of state or molecular simulations, is a challenge for the prediction of thermodynamic properties. As the number of components and their respective complexity increase, it becomes impractical to fit all the unlike interactions. Lorentz-Berthelot combining rules work well for systems, where the main interactions are dispersion forces, but they do not account for electrostatics. In this work, we derive predictive combining rules within the SAFT-γ-Mie framework. In the resulting model, the unlike-pair interactions account for the effect of ionization energies, partial charges, dipole moments, and quadrupole moments. We then estimate these properties for molecular fragments using density functional theory calculations and demonstrate their use to obtain realistic cross-interaction energies without the need for experimental data. An open-source python package, Multipole Approach to Predictively Scale Cross-Interactions, is included to facilitate use of the methods presented in this work. A good qualitative agreement was obtained for all phase equilibria calculations of binary mixtures containing carbon dioxide with propane, hexane, benzene, and water, as well as mixtures of hexane and benzene. Finally, we discuss future improvements to our methodology, including the use of physical insights when fitting self-interaction parameters.

Oligomer/Polymer Blend Phase Diagram and Surface Concentration Profiles for Squalane/Polybutadiene: Experimental Measurements and Predictions from SAFT-γ Mie and Molecular Dynamics Simulations

The compatibility and surface behavior of squalane-polybutadiene mixtures are studied by experimental cloud point and neutron reflectivity measurements, statistical associating fluid theory (SAFT), and molecular dynamics (MD) simulations. A SAFT-γ Mie model is shown to be successful in capturing the cloud point curves of squalane-polybutadiene and squalane-cis-polybutadiene binary mixtures, and the same SAFT-γ Mie model is used to develop a thermodynamically consistent top-down coarse-grained force field to describe squalane-polybutadiene. Coarse-grained molecular dynamics simulations are performed to study surface behavior for different concentrations of squalane, with the system exhibiting surface enrichment and a wetting transition. Simulated surface profiles are compared with those obtained by fitting to neutron reflectivity data obtained from thin films composed of deuterated squalane (d-sq)-polybutadiene. The presented top-down parametrization methodology is a fast and thermodynamically reliable approach for predicting properties of oligomer-polymer mixtures, which can be challenging for either theory or MD simulations alone.

Equation of state and force fields for Feynman-Hibbs-corrected Mie fluids. II. Application to mixtures of helium, neon, hydrogen, and deuterium

We extend the statistical associating fluid theory of quantum corrected Mie potentials (SAFT-VRQ Mie), previously developed for pure fluids [Aasen et al., J. Chem. Phys. 151, 064508 (2019)], to fluid mixtures. In this model, particles interact via Mie potentials with Feynman-Hibbs quantum corrections of first order (Mie-FH1) or second order (Mie-FH2). This is done using a third-order Barker-Henderson expansion of the Helmholtz energy from a non-additive hard-sphere reference system. We survey existing experimental measurements and ab initio calculations of thermodynamic properties of mixtures of neon, helium, deuterium, and hydrogen and use them to optimize the Mie-FH1 and Mie-FH2 force fields for binary interactions. Simulations employing the optimized force fields are shown to follow the experimental results closely over the entire phase envelopes. SAFT-VRQ Mie reproduces results from simulations employing these force fields, with the exception of near-critical states for mixtures containing helium. This breakdown is explained in terms of the extremely low dispersive energy of helium and the challenges inherent in current implementations of the Barker-Henderson expansion for mixtures. The interaction parameters of two cubic equations of state (Soave-Redlich-Kwong and Peng-Robinson) are also fitted to experiments and used as performance benchmarks. There are large gaps in the ranges and properties that have been experimentally measured for these systems, making the force fields presented especially useful.

Statistical Mechanical Model for Adsorption Coupled with SAFT-VR Mie Equation of State

We extend the SAFT-VR Mie equation of state to calculate adsorption isotherms by considering explicitly the residual energy due to the confinement effect. Assuming a square-well potential for the fluid-solid interactions, the structure imposed by the fluid-solid interface is calculated using two different approaches: an empirical expression proposed by Travalloni et al. ( Chem. Eng. Sci. 65 , 3088 - 3099 , 2010 ), and a new theoretical expression derived by applying the mean value theorem. Adopting the SAFT-VR Mie ( Lafitte et al. J. Chem. Phys. , 139 , 154504 , 2013 ) equation of state to describe the fluid-fluid interactions, and solving the phase equilibrium criteria, we calculate adsorption isotherms for light hydrocarbons adsorbed in a carbon molecular sieve and for carbon dioxide, nitrogen, and water adsorbed in a zeolite. Good results are obtained from the model using either approach. Nonetheless, the theoretical expression seems to correlate better the experimental data than the empirical one, possibly implying that a more reliable way to describe the structure ensures a better description of the thermodynamic behavior.

On the use of molecular-based thermodynamic models to assess the performance of solvents for CO2 capture processes: monoethanolamine solutions

Predictive models play an important role in the design of post-combustion processes for the capture of carbon dioxide (CO₂) emitted from power plants. A rate-based absorber model is presented to investigate the reactive capture of CO₂ using aqueous monoethanolamine (MEA) as a solvent, integrating a predictive molecular-based equation of state: SAFT-VR SW (Statistical Associating Fluid Theory-Variable Range, Square Well). A distinctive physical approach is adopted to model the chemical equilibria inherent in the process. This eliminates the need to consider reaction products explicitly and greatly reduces the amount of experimental data required to model the absorber compared to the more commonly employed chemical approaches. The predictive capabilities of the absorber model are analyzed for profiles from 10 pilot plant runs by considering two scenarios: (i) no pilot-plant data are used in the model development; (ii) only a limited set of pilot-plant data are used. Within the first scenario, the mass fraction of CO₂ in the clean gas is underestimated in all but one of the cases, indicating that a best-case performance of the solvent can be obtained with this predictive approach. Within the second scenario a single parameter is estimated based on data from a single pilot plant run to correct for the dramatic changes in the diffusivity of CO₂ in the reactive solvent. This parameter is found to be transferable for a broad range of operating conditions. A sensitivity analysis is then conducted, and the liquid viscosity and diffusivity are found to be key properties for the prediction of the composition profiles. The temperature and composition profiles are sensitive to thermodynamic properties that correspond to major sources of heat generation or dissipation. The proposed modelling framework can be used as an early assessment of solvents to aid in narrowing the search space, and can help in determining target solvents for experiments and more detailed modelling.