Machine Learning Approaches for Prediction of Phase Equilibria in Poly (Ethylene Glycol) + Sodium Phosphate Aqueous Two-Phase Systems

Document Type : Research Article

Authors

1 Chemical Engineering Department, Faculty of Engineering, Shomal University, PO Box 731 Amol, I.R. IRAN

2 Faculty of Chemical Engineering and Environmental Protection "Cristofor Simionescu", "Gh. Asachi" Technical University, Bld Mangeron 73, 700050, Iasi, ROMANIA

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 the NRTL model, and are between 0.0083 and 0.0153 for UNIQUAC model.

Keywords

Main Subjects

References

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Iranian Journal of Chemistry and Chemical Engineering
Volume 39, Issue 6 - Serial Number 104
November and December 2020
Pages 185-197

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