Development of the NRTL functional activity coefficient (NRTL-FAC) model using high quality and critically evaluated phase equilibria data. 2

Abstract

One of the most significant models based on the local composition concept in advanced thermodynamics, is the non-random two-liquid (NRTL) model. Many studies have been conducted to enhance its applicability to various systems. Among these studies, the development of the NRTL model for electrolytic systems, polymer systems, and systems containing special chemical associations has been particularly significant. However, the NRTL model and its developed forms are based on the concept of local composition, and the dependency of these models on the experimental data for regressing NRTL interaction parameters limits their applicability of the NRTL model. Accordingly, to overcome this limitation, the NRTL functional activity coefficient model (NRTL-FAC), which is a group contribution model, was developed (https://doi.org/10.1016/j.fluid.2021.113088). The current study aims to extend the NRTL-FAC model. To achieve this, 15 new main groups have been added to the previous ones, and 266 new interaction parameters have been optimized. A total of 374 isothermal/isobaric VLE data sets, including 7115 data points, were used. The quality of the experimental VLE data was assessed using various thermodynamic consistency tests, including the Herington test, Van Ness test, point test, infinite dilution test, EoS test, and endpoint test. The NRTL-FAC model can accurately predict the VLE of binary systems, with results in good agreement with experimental data at different temperature and pressure ranges. This accuracy was observed for both azeotrope systems and ideal systems with positive or negative deviation from Raoult's law. Unlike the UNIFAC-DMD model, which restricts a portion of its interaction parameters to consortium members, the NRTL-FAC model interaction parameters are publicly accessible. Therefore, the NRTL-FAC model can be confidently used as a preliminary estimate to predict VLE behavior in process design when experimental data is not available.