Experimental data, thermodynamic and neural network modeling of CO2 solubility in aqueous sodium salt of l-phenylalanine

• Main Authors: Garg, S., Shariff, A.M., Shaikh, M.S., Lal, B., Suleman, H., Faiqa, N.
• Format: Article
• Published: Elsevier Ltd 2017
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016434935&doi=10.1016%2fj.jcou.2017.03.011&partnerID=40&md5=d7123aac407012796927e1e5ca6fc010; http://eprints.utp.edu.my/19504/

In this study, experimental CO2 solubility in aqueous sodium salt of l-phenylalanine (Na-Phe) was investigated at concentrations (w = 0.10, 0.20, and 0.25) mass fractions. The solubility was measured in a high-pressure solubility cell at temperatures 303.15, 313.15 and 333.15 K, over a CO2 pressure range of (2-25) bar. The effect of temperature, equilibrium CO2 pressure and Na-Phe concentration on CO2 loading were examined. Two different models namely modified Kent-Eisenberg and artificial neural network (ANN) were used to correlate the CO2 solubility data. Carbamate hydrolysis and amine deprotonation equilibrium constants were estimated as a function of temperature, pressure and solvent concentration from modified Kent-Eisenberg model. Also, the comparison of prediction results obtained from both modeling techniques was carried out. It was found that ANN model performed better than modified Kent-Eisenberg model. © 2017 Elsevier Ltd. All rights reserved.