New strategy for predicting liquid–liquid equilibrium near critical point using global renormalization group theory

Abstract

Classical liquid activity coefficient models, such as the nonrandom two-liquid (NRTL) model, fail near the critical point of the liquid–liquid equilibrium (LLE), unless a highly nonlinear temperature dependency is introduced for the molecular interaction parameters. In this work, we propose an approach to predict the LLE data near the critical point using data away from the critical region based on the global renormalization group theory (GRGT). Specifically, we propose a non-empirical approach to determine the GRGT parameters, which does not rely on experimental data. The performance of our method is examined using the NRTL model on 21 binary mixtures. Our results show that the predictive approach proposed in this work reduces the error in the critical solution temperatures by about 48% when compared to the classical NRTL model with linear temperature-dependent interaction parameters.