Predictive Molecular Simulation Studies on the Vapor–Liquid Equilibria of 10 Binary Mixtures Containing Different Hydrofluoroolefins

In this work, predictions from Gibbs Ensemble Monte Carlo simulations on the vapor liquid phase equilibria properties of 10 different binary mixtures of the components, carbon dioxide, 2,3,3,3-tetrafluoropropene (R-1234yf), cis-and trans-1,3,3,3-tetrafluoropropene [R-1234ze(Z/E)], cis- and trans-1,1,1,4,4,4-hexafluorobut-2-ene [R-1336mzz(Z/E)], and trans-1-chloro-3,3,3-trifluoroprop-1-ene [R-1233zd(E)], are presented. For seven of these mixtures, the simulation results represent the first information on their phase behavior, addressing gaps in the existing data on potential HFO-based refrigerant blends. The simulation results together with available experimental data were then used to derive parameters for the multifluid modeling of these mixtures. Different variants of the multifluid model, i.e., predictive mixing rules as well as different parametrizations of the adjustable parameters, are evaluated by assessing their performance in reproducing bubble and dew point lines, as well as saturated densities.