ABSTRACT
Fluid phase equilibria and mixing properties are of primary interest for theoretical purposes (mathematical model design, parameter estimation, etc.), and for the development of a general proper liquid theory. In chemical industrial processes involving liquid mixtures, the optimization and adequate design of separation
Equipments are conditioned by a sufficient knowledge of mixing thermodynamics (Iglesias et al., 2007). In what is referred to the unit operation field, the optimization of separation operations by extraction or distillation, require knowledge of the twoliquids phase equilibria, and thermodynamics, which can be determined either experimentally or by prediction based on an appropriate model, and a set of data. Artificial neural networks (ANNs) can also predict liquid-liquid equilibrium (LLE) data as well as thermodynamic model and it dose not have the difficulties equation of state, EOS, model for obtain thermodynamic parameter.
