Prediction of liquid-liquid equilibrium for multicomponent systems including ionic liquids by the ASOG method
Monday, April 27, 2015
Aventine Ballroom ABC/Grand Foyer, Ballroom Level
Mrs. Dalia Danithza Gallardo Ramirez1, Dr. Martin Aznar2 and Dr. Maria Alvina Krähenbühl2, (1)Departamento de Desenvolvimento de Processos e Produtos (DDPP), UNIVERSIDADE ESTADUAL DE CAMPINAS, CAMPINAS, (2)Departamento de Desenvolvimento de Processos e Produtos (DDPP)- Engenharia Química, UNIVERSIDADE ESTADUAL DE CAMPINAS, CAMPINAS
Liquid-liquid equilibrium phase in multicomponent systems is very important in industrial processes involving liquid extraction, this requires a larger amount of solvent. Ionic liquids are chemical compounds consisting of ions with many interesting properties which make them have the potential to replace the traditional organic solvents. For the synthesis, development and optimization of chemical and industrial processes requires a real understanding of the behavior of the substances involved in the process during the phase equilibrium. However, experimental data are not always available in the literature. Due to this property estimation methods are commonly used , they are based on correlations. The thermodynamic models of group contribution are widely used to estimate properties, especially the activity coefficient, essential for the prediction of vapor-liquid equilibrium and the liquid-liquid equilibrium. The main objective in the present work  is to predict liquid-liquid equilibrium data from existing data of multicomponent systems containing ionic liquids, using the Analytical Solution of Groups (ASOG) method to get the parameters and activity coefficients of other systems, for which no experimental information is available. The group interaction parameters can be estimated by using the Fortran code TML-LLE 2.0 ; the procedure is based on the Simplex method, and consists in the minimization of a concentration-based objective function, using the mean square deviation (rms) between the experimental and calculated composition of each component phases. Met relative errors less than 5%, which would be very satisfactory in the case of a group contribution method.