Liquid-liquid equilibrium study for ternary systems of (water + furfuryl alcohol + solvents) at 298.2 K: Measurement and thermodynamic modelling. (September 2020)

• Record Type: Journal Article
• Authors: Dong, Shihua; Sun, Weizhen; Jiang, Yueyang; Jia, Bing
• Is Part Of: Journal of chemical thermodynamics. Volume 148(2020)
• Publication Date: 2020-09
• Subjects: Liquid-liquid equilibria -- Furfuryl alcohol -- Isopropyl ether -- Tert-butyl methyl ether -- Dichloromethane -- Methyl isobutylcarbinol; Thermodynamics -- Periodicals; Thermochemistry -- Periodicals; Thermodynamique -- Périodiques; Thermochimie -- Périodiques; Thermochemistry; Thermodynamics; Periodicals; 541.369
• DOI: 10.1016/j.jct.2020.106136
• Languages: English
• ISSNs: 0021-9614

Abstract

Highlights: The LLE data for water + TFP + DIPE/MTBE/CH2 Cl2 /MIBC were measured. The distribution coefficient and selectivity were calculated. The reliability of LLE data were verified by the Othmer-Tobias, Bachman and Hand equations. The NRTL and UNIQUAC models were applied to correlate the experimental LLE data. The binary interaction parameter values were obtained from the data correlation. Abstract: Liquid-liquid equilibrium (LLE) data for {water + furfuryl alcohol + solvent (isopropyl ether, tert-butyl methyl ether, dichloromethane and methyl isobutylcarbinol)} ternary systems were determined at T = 298.2 K and p = 101.3 kPa. The distribution coefficients and separation factors were evaluated and the results showed that those solvents can effectively for furfuryl alcohol recovery from aqueous solutions. The Othmer-Tobias, Bachman and Hand equations were employed to validate the reliability of the experimental LLE data. Additionally, the experimental LLE data were correlated using the NRTL and UNIQUAC models and the binary interaction parameters were optimized. The root mean square deviations (RMSD) between the correlated data by NRTL and UNIQUAC models and the experimental LLE data were less than 0.36%, which demonstrated that both models can correlate experimental LLE data successfully.