Liquid–Liquid Equilibrium Data Correlation Using NRTL Model for Different Types of Binary Systems: Upper Critical Solution Temperature, Lower Critical Solution Temperature, and Closed Miscibility Loops

Abstract

In this work, LLE data at different temperatures have been correlated for 30 binary systems that presented different miscibility behaviour: 15 upper critical solution temperature (UCST), 5 critical solution temperature (LCST) and 10 closed loop LLE region systems. The NRTL model along with an expression frequently used in literature for the temperature dependence in the binary interaction has allowed an acceptable fitting of all the systems. The parameters obtained have been validated by both the inspection of the Gibbs energy of mixing function regarding the fulfilment of the Gibbs common tangent equilibrium condition, and also the stability of the solution to avoid possible metastable equilibrium solutions. The critical solution temperatures have been calculated by extrapolation using the NRTL parameters obtained for all selected binary systems.Moreover, the NRTL parameter values have been analysed using some proposed representations that also include the boundary curve between miscible (L) and partially miscible (LLE) regions. These graphical representations are useful because they show the parameter value requirements to reproduce UCST, LCST or closed loop behaviours.

A Geometric Approach for the Calculation of the Nonrandomness Factor Using Computational Chemistry

“…The most well-known example is the Nonrandom Two-Liquid (NRTL) model, which was proposed by H. Renon and J.M. Prausnitz in 1968 and takes into account the nonrandomness of the interactions between particles of similar and different types. , It is widely used to describe liquid–liquid equilibria (LLE) − and vapor–liquid equilibria (VLE) − and requires three parameters for a binary system: two binary interaction parameters (BIPs) and the nonrandomness factor (α)…”