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

Garg, S. and Shariff, A.M. and Shaikh, M.S. and Lal, B. and Suleman, H. and Faiqa, N. (2017) Experimental data, thermodynamic and neural network modeling of CO2 solubility in aqueous sodium salt of l-phenylalanine. Journal of CO2 Utilization, 19. pp. 146-156.

Full text not available from this repository.
Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

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. © 2017 Elsevier Ltd. All rights reserved.

Item Type: Article
Impact Factor: cited By 5
Departments / MOR / COE: Division > Academic > Faculty of Engineering > Chemical Engineering
Depositing User: Mr Ahmad Suhairi Mohamed Lazim
Date Deposited: 20 Apr 2018 06:04
Last Modified: 20 Apr 2018 06:04
URI: http://scholars.utp.edu.my/id/eprint/19504

Actions (login required)

View Item
View Item