Title of article
Machine Learning Approaches for Prediction of Phase Equilibria in Poly (Ethylene Glycol) + Sodium Phosphate Aqueous Two-Phase Systems
Author/Authors
Pirdashti ، Mohsen Chemical Engineering Department - Faculty of Engineering - Shomal University , Taheri ، Mojtaba Chemical Engineering Department - Faculty of Engineering - Shomal University , Dragoi ، Niculina Faculty of Chemical Engineering and Environmental Protection Cristofor Simionescu - Gh. Asachi Technical University , Curteanu ، Silvia Faculty of Chemical Engineering and Environmental Protection Cristofor Simionescu - Gh. Asachi Technical University
From page
185
To page
197
Abstract
In this research, liquid-liquid equilibrium (LLE) data were experimentally obtained for the ternary systems of (water + carboxylic acid + dipropyl ether) at T = 298.2 K and P = 101.3 kPa. The carboxylic acids used in this study were isobutyric acid, valeric acid and isovaleric acid. All these systems are according to Treybal classification, Type-2 systems because the two binary subsystems are partially miscible. The lowest distribution coefficients and separation factors were calculated for isobutyric acid (40 and 329, respectively). The authenticity of the experimental equilibrium data was identified from Hand and Othmer-Tobias correlations. The experimental tie line data were correlated by using the nonrandom two-liquid (NRTL) and universal quasi-chemical (UNIQUAC) activity coefficient models. RMSD values are between 0.0112 and 0.0155 for NRTL model; and are between 0.0083 and 0.0153 for UNIQUAC model.
Keywords
Liquid , liquid equilibrium , Carboxylic acid , Dipropyl ether , NRTL , UNIQUAC
Journal title
Iranian Journal of Chemistry and Chemical Engineering (IJCCE)
Journal title
Iranian Journal of Chemistry and Chemical Engineering (IJCCE)
Record number
2528061
Link To Document