Vapor-liquid Equilibrium Data For Binary Mixtures Research Articles

Vapor–Liquid Equilibria for the Binary and Ternary Systems of Difluoromethane (R32), 1,1-Difluoroethane (R152a), and 2,3,3,3-Tetrafluoroprop-1-ene (R1234yf)

The combination of difluoromethane (R32), 1,1-difluoroethane (R152a), and 2,3,3,3-tetrafluoroprop-1-ene (R1234yf) could be a potential substitute for hydro-fluorocarbon refrigerants. Reliable vapor liquid equilibrium (VLE) data are important thermodynamic data in evaluating the performance of refrigeration cycles and determining their optimal compositions. In this work, we measured the VLE data for binary mixtures of R32 + R152a and R152a + R1234yf, and ternary system of R32 + R152a + R1234yf. The measurements were carried out by using the AnTLcirCapValVis analytical method over the temperature range from 283.15 to 323.15 K. The standard uncertainties of temperature, pressure, and mole fractions are 10 mK, 0.5 kPa, and 0.005, respectively. The Peng–Robinson–Stryjek–Vera equation of state combined with the Wong–Sandler mixing rule and the nonrandom two-liquid activity coefficient model was employed to correlate the parameters of binary mixtures and predict the ternary VLE property. The predicted VLE data and K-value for the ternary system show good agreement with the experimental results.

Use of a hybrid optimization method to reduce vapor–liquid equilibrium data of maverick systems: The case of carbon dioxide with 2-methoxyethanol and 2-ethoxyethanol using cubic equations of state

Using a hybrid of the Genetic Algorithm (GA) and the Fmincon optimization techniques is proposed for reducing vapor liquid equilibrium (VLE) data of systems formed by a subcritical and a supercritical compound. As an example, this hybrid technique is used with advantage for evaluation of binary parameters required by cubic equations of state for the correlation of VLE data of binary mixtures containing carbon dioxide with 2-methoxyethanol and 2-ethoxyethanol. Four cubic equations of state (modified Van der Waals, Soave–Redlich–Kwong, Peng–Robinson, and Peng–Robinson–Stryjek–Vera), coupled with four mixing rules (conventional one-binary parameter, Margules-type, Huron–Vidal and the reformulated Wong–Sandler) were used. The Peng–Robinson–Stryjek–Vera EoS coupled with the Margules-type mixing rule gave the best correlation of vapor phase composition and combined with the reformulated Wong–Sandler mixing rule gave the best correlation of equilibrium pressure. The latter combination gave the best overall fit of the data. The binary interaction parameters were found to be independent of temperature.

Vapor–liquid equilibrium for the ternary carbon dioxide–ethanol–nonane and decane systems

In this work, experimental vapor–liquid equilibrium (T, p, xi, yi) data for the ternary carbon dioxide–ethanol–nonane and carbon dioxide–ethanol–decane systems are reported in the temperature range of 313–373K from low pressures to the nearest of the corresponding critical pressure. Measurements were performed in an apparatus based on the static-analytic method with an on-line ROLSI sampler-injector device. Vapor–liquid equilibrium (VLE) data for both ternary systems are predicted using the Peng–Robinson equation of state coupled to the Wong–Sandler, one parameter van der Waals and two parameters van der Waals mixing rules. Binary interaction parameters are obtained from the VLE data of binary mixtures reported in the literature.

Using an Adaptive Parameter Method for Process Simulation of Nonideal Systems

A thermodynamic model of the ϕ/ϕ class of methods that can be easily used with commercial process simulators is proposed. The vapor−liquid equilibrium (VLE) is calculated by means of a Redlich−Kwong-type equation of state (EoS) that uses modified Huron−Vidal mixing rules with activity coefficients: the activity coefficients are derived from the NRTL model whose parameters are evaluated by fitting VLE data of binary mixtures. By means of the Aspen PLUS process simulator, a comparison is made between the performances of both the proposed method with user-created adaptive parameters that can be forced into the simulator database and the Predictive−Soave−Redlich−Kwong (PSRK) method that uses UNIFAC to compute the excess free energy. The ethanol−water separation by extractive distillation is analyzed to point out how an incorrect prediction of the azeotrope can lead to underestimation of the overall process energy requirement.