Abstract
In this work, we present a novel approach to predict the location of azeotropes for binary mixtures using the perturbed-chain statistical associating fluid theory equation of state (PC-SAFT).The proposed method requires as input the pure-component parameters of the PC-SAFT equation: the segment number (m), the hard-core segment diameter (σ), and the segment-segment interaction energy parameter (ε/k) for every pure non-associating fluid. By using these parameters, PC-SAFT estimates with accuracy the azeotropes properties of binary mixtures as well as the successful prediction of vapour-liquid equilibria for many non-associating binary systems. In order to improve the predictive ability of the PC-SAFT equation, the interaction parameters of 8 binary systems containing novel refrigeration fluid, were estimated from binary vapour–liquid equilibrium data. For comparison, the data were also modelled using the (PR-MC-WS-NRTL) thermodynamic model. Good agreements are found between the calculated results and reference data and the relative error does not exceed 3.69% and 0.97% for the molar fraction and the pressure respectively.
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