No abstract

In this work a new method for inclusion of pressure effects in COSMO-type activity coefficient models is proposed. The extension consists in the direct combination of COSMO-SAC and lattice-fluid ideas by the inclusion of free volume in form of holes. The effort when computing pressure (given temperature, volume, and mole numbers) with the proposed model is similar to the cost for computing activity coefficients with any COSMO-type implementation. For given pressure, computational cost increases since an iterative method is needed. This concept was tested for representative substances and mixtures, ranging from light gases to molecules with up to 10 carbons. The proposed model was able to correlate experimental data of saturation pressure and saturated liquid volume of pure substances with deviations of 1.16% and 1.59%, respectively. In mixture vapor-liquid equilibria predictions, the resulting model was superior to Soave-Redlich-Kwong with Mathias-Copeman a-function and the classic van der Waals mixing rule in almost all cases tested and similar to PSRK method, from low pressures to over 100 bar. Good predictions of liquid-liquid equilibrium were also observed, performing similarly to UNIFAC-LLE, with improved responses at high temperatures and pressures.

COSMO-RS refinements and applications have been the focus of numerous works, mainly due to their great predictive capacity. However, these models do not directly include pressure effects. In this work, a methodology for the inclusion of pressure effects in the functional-segment activity coefficient model, F-SAC (a COSMO-based group-contribution method), is proposed. This is accomplished by the combination of F-SAC and lattice-fluid ideas by the inclusion of free volume in the form of holes, generating the F-SAC-Phi model. The computational cost when computing the pressure (given temperature, volume, and molar volume) with the proposed model is similar to the cost for computing activity coefficients with any COSMO-type implementation. For a given pressure, the computational cost increases since an iterative method is needed. The concept is tested for representative substances and mixtures, ranging from light gases to molecules with up to 10 carbons. The proposed model is able to correlate experimental data of saturation pressure and saturated liquid volume of pure substances with deviations of 1.7 and 1.1%, respectively. In the prediction of mixture vapor−liquid equilibria, the resulting model is superior to COSMO-SAC-Phi, SRK-MC (Soave−Redlich−Kwong with the Mathias−Copeman α-function) with the classic van der Waals mixing rule, and PSRK in almost all tested cases, from low pressures to over 100 bar.