Assessment of the Perturbed Chain-Statistical Associating Fluid Theory Equation of State against a Benchmark Database of High-Quality Binary-System Data

The effect of confinement on the phase behavior of propane in nanoporous media: an experimental study probing capillary condensation, evaporation, and hysteresis at varying pore sizes and temperatures

Fundamental understanding of the phase behavior and properties of fluids under confinement is of great significance for multiple fields of engineering and science, as well as for many practical industrial applications. In particular, unconventional geological systems, such as shale reservoirs, possess nanometer-scale pores, which impose nanoconfinement on the fluid molecules. In large pores, the bulk phase behavior of fluids can be modeled by the well-established methods, such as equation of state (EOS) approaches. However, under confinement the thermodynamic properties of fluids deviate significantly from those in the bulk, thus rendering the traditional EOS methods ineffective in predicting the phase behavior of confined fluids. Recently, the PC-SAFT/Laplace EOS has been developed to better represent the fluid phase equilibria in nanopores, which incorporates a new parameter that needs to be determined from experimental data. In this study, a new dataset is presented to reflect the phase properties of propane confined within the MCM-41 pores, with the aim to improve both the general understanding of the phase behavior of hydrocarbons under confinement and to parameterize the PC-SAFT/Laplace EOS for the nanoconfined propane. For this purpose, propane adsorption and desorption isotherms are determined experimentally for a wide range of temperatures (-27 to 20 °C) in MCM-41 of three different pore sizes (nominal pore diameters of 60, 80, and 100 Å). The effects of temperature and pore diameter on the capillary condensation and evaporation pressures are discussed in detail. Furthermore, the adsorption-desorption hysteresis behavior and its progression for different pore sizes were discussed. The experimental data are modeled using the parameterized PC-SAFT/Laplace EOS, which accurately captured the effects of confinement on the capillary condensation of propane in MCM-41. In addition, this study enriches the field of nanoconfinement research by providing a new dataset exemplifying the thermodynamic characteristics of hydrocarbons in nanopores.

Purely Predicting the Pharmaceutical Solubility: What to Expect from PC-SAFT and COSMO-RS?

A pair of popular thermodynamic models for pharmaceutical applications, namely, the perturbed-chain statistical associating fluid theory (PC-SAFT) equation of state and the conductor-like screening model for real solvents (COSMO-RS) are thoroughly benchmarked for their performance in predicting the solubility of active pharmaceutical ingredients (APIs) in pure solvents. The ultimate goal is to provide an illustration of what to expect from these progressive frameworks when applied to the thermodynamic solubility of APIs based on activity coefficients in a purely predictive regime without specific experimental solubility data (the fusion properties of pure APIs were taken from experiments). While this kind of prediction represents the typical modus operandi of the first-principles-aided COSMO-RS, PC-SAFT is a relatively highly parametrized model that relies on experimental data, against which its pure-substance and binary interaction parameters (k_ij) are fitted. Therefore, to make this benchmark as fair as possible, we omitted any binary parameters of PC-SAFT (i.e., k_ij = 0 in all cases) and preferred pure-substance parameter sets for APIs not trained to experimental solubility data. This computational approach, together with a detailed assessment of the obtained solubility predictions against a large experimental data set, revealed that COSMO-RS convincingly outperformed PC-SAFT both qualitatively (i.e., COSMO-RS was better in solvent ranking) and quantitatively, even though the former is independent of both substance- and mixture-specific experimental data. Regarding quantitative comparison, COSMO-RS outperformed PC-SAFT for 9 of the 10 APIs and for 63% of the API-solvent systems, with root-mean-square deviations of the predicted data from the entire experimental data set being 0.82 and 1.44 log units, respectively. The results were further analyzed to expand the picture of the performance of both models with respect to the individual APIs and solvents. Interestingly, in many cases, both models were found to qualitatively incorrectly predict the direction of deviations from ideality. Furthermore, we examined how the solubility predictions from both models are sensitive to different API parametrizations.