Vapor-liquid equilibrium data for systems of hyperbranched polymer (HBP) and carbon dioxide are reported for temperatures of 285-455 K and pressures up to 13 MPa. The bubble-point pressures of (CO2 + hyperbranched polyester) and of (CO2 + hyperbranched polyglycerol + CH3OH) samples with fixed compositions were measured using a Cailletet apparatus. The system (CO2 + polyglycerol + CH3OH) also exhibits a liquid-liquid phase split characterized by lower critical solution temperatures. For this system cloud point curves and vapor-liquid-liquid bubble-point curves were also measured. Moreover, a thermodynamic model has been developed for HBP mixtures in the framework of the perturbed-chain polar statistical association fluid theory (PCP-SAFT) equation of state accounting for branching effects. There is no additional binary interaction parameter introduced along with the branching contributions to the model. Although the miscibility gap in the system (CO2 + polyglycerol + CH3OH) is not predicted by the model, PCP-SAFT including branching effects gives a good representation of the bubble-point curves of this system at temperatures lower than the lower solution temperature (LST).
Infinite dilution activity coefficients can be determined relatively fast from several experimental techniques. Literature values for the infinite dilution activity coefficients are used to determine a binary interaction parameter of the perturbed-chain polar statistical associating fluid theory (PCP-SAFT) equation of state. The model is, subsequently, applied to the full concentration range of binary mixtures, and the results are compared to experimental data from literature. The applicability of the method is demonstrated for examples involving polar, associating, and polymeric components. It is confirmed that the parametrization allows for extrapolations in temperature. In combination with a group-contribution model for the estimation of infinite dilution activity coefficients (e.g., modified UNIFAC(Do)), the equation of state can be used to predict vapor−liquid equilibria of mixtures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.