Experimental data, thermodynamic and neural network modeling of CO 2 solubility in aqueous sodium salt of l -phenylalanine

Sahil Garg, Azmi Mohd Shariff, Muhammad Shoaib Shaikh, Bhajan Lal, Humbul Suleman, Nor Faiqa

Research output: Contribution to journalArticle

Abstract

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.
Original languageEnglish
Pages (from-to)146-156
Number of pages11
JournalJournal of CO2 Utilization
Volume19
DOIs
Publication statusPublished - 1 May 2017

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