Adaptive intermolecular interaction parameters for accurate Mixture Density Functional Theory calculations

The description of fluid mixtures molecular behavior is significant for various industry fields due to the complex composition of fluid found in nature. Statistical mechanics approaches use intermolecular interaction potential to predict fluids behavior on the molecular scale. The paper provides a comparative analysis of mixing rules applications for obtaining intermolecular interaction parameters of mixture components. These parameters are involved in the density functional theory equation of state for mixtures (Mixture DFT EoS) and characterize thermodynamic mixture properties in the bulk. The paper demonstrates that Mixture DFT EoS with proper intermolecular parameters agrees well with experimental mixtures isotherms in bulk: Ar + Ne, CO2 + CH4, CO2 + C(2)H6 and CH4 + C(2)H6 However, predictions of vapor-liquid equilibrium (VLE) experimental data for CO2 + C4H10 are not successful. Halgren HHG, Waldman-Hagler, and adaptive mixing rules that adjust on the experimental data from the literature are used for the first time to obtain intermolecular interaction parameters for the mixture DFT model. The results obtained provide a base for understanding how to validate the DFT fluid mixture model for calculating thermodynamic properties of fluid mixtures on a micro and macro scale. (c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

The description of fluid mixtures molecular behavior and the calculation of their thermodynamic properties are of great importance. This paper provides a comparative analysis of mixing rules and obtains intermolecular interaction parameters for mixture components. It demonstrates the predictive capability of a mixture DFT model and highlights the challenges in predicting vapor-liquid equilibrium experimental data.