174
Ind. Eng. Chem. Process Des. Dev. 1982, 21 174-180
Prediction and Correlation of Liquid-Liquid Equilibria Jose Slmonetty,' Davld Yee, and Dlmltrlos Tasslos Department of Chemical Engineering and Chemistry, New Jersey Institute of Technobgy, Newark, New Jersey 07102
The NRTL, LEMF, and UNIQUAC models are used in the prediction and correlation of liquid-liquid equilibrium data for ten type Isystems. The results Indicate that best predictions are obtained with the LEMF equation, with an overall average absolute percentage error in distribution coefficients of 19.5 as compared to 23.0 and 24.7 with the NRTL and UNIQUAC equations, respectively. Good correlation of liquid-liquid equilibrium data alone is obtained with all three models; the LEMF equation is slightly better with an overall average absolute percentage error in distribution coefflcients of 5.5 as compared to 6.7 and 5.9 for the NRTL and UNIQUAC equations, respectively. The same applies for the simultaneous correlation of liquid-liquid and binary vapor-liquid equilibrium data, where the combined errors for the distribution and activity coefficients are LEMF, 6.5; NRTL, 8.8; and UNIQUAC, 8.2. In all cams best results are obtained for systems having large mutual solubilities, and become progressively worse as the mutual solubility decreases.
Introduction Prediction and f or correlation of multicomponent liquid-liquid equilibrium (LLE) is of importance in chemical engineering applications such as extraction and, when combined with vapor-liquid equilibrium (VLE) data, for extractive or azeotropic distillation. Several authors, using different models for the excess Gibbs free energy, have dealt with this problem with varying degrees of success (Renon and Prausnitz, 1968; Joy and Kyle, 1969; Joy and Kyle, 1970; Cohen and Renon, 1970; Marina and Tassios, 1973; Hiranuma, 1974; Van Zandijcke and Verhoeye, 1974; Bender and Block, 1975; Abrams and Prausnitz, 1975; Nagata and Ogura, 1975; Tsuboka and Katayama, 1975; Nagata and Nagashima, 1976; DeFre and Verhoeye, 1976; Sugi and Katayama, 1976; Newsham and Vahdat, 1977; DeFre and Verhoeye, 1977; Sugi and Katayama, 1977; Anderson and Prausnitz, 1978; Sugi and Katayama, 1978; Soerensen et al., 1979a,b; Soerensen and Arlt, 1979; Tochigi et al., 1980; Magnussen et al., 1980; and Prausnitz et al., 1980). Prediction of LLE is also possible with the UNIFAC model. However, Magnussen et al. (1980) conclude that quantitative prediction of LLE data with the UNIFAC model is possible only when the group interaction parameters are based on LLE data. Their results show that for ternary systems, the absolute difference between the predicted and experimental mole fractions is on the average four times larger than that obtained with the UNIQUAC equation with a total of six adjustable parameters fitted to the ternary data. Ternary LLE systems are classified according to the number of partially miscible binary systems (PMBS) into three types: type I (one PMBS), type I1 (two PMBS), and type I11 (three PMBS). Type I11 systems are rarely found in chemical engineering applications, and type I1 systems can be successfully handled in terms of prediction and correlation with the models used by the above authors; therefore, this study is focused on type I systems. An evaluation of the prediction performance of the most successful models (NRTL, Renon and Prausnitz, 1968; LEMF, Marina and Tassios, 1973; and UNIQUAC, Anderson and Prausnitz, 1978) suggests that it would be convenient to classify type I systems into three categories (LA, IB,and IC) according to the breadth of the two-phase region as shown in Figure 1. To complete this classifi-
* Correspondence should be addressed to this author at 364 Roseville Ave., Newark, NJ 07107. 0196-4305/82/1121-0174$01.25/0
Table I. Mutual Solubility Ranges Used to Classify Systems as Type IA, IB, and IC system type
x,'
IA IB IC
>0.01
X*II
0.86 >0.99
>0.01
