relation: https://khub.utp.edu.my/scholars/8693/
title: Experimental data, thermodynamic and neural network modeling of CO2 solubility in aqueous sodium salt of l-phenylalanine
creator: Garg, S.
creator: Shariff, A.M.
creator: Shaikh, M.S.
creator: Lal, B.
creator: Suleman, H.
creator: Faiqa, N.
description: 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.
publisher: Elsevier Ltd
date: 2017
type: Article
type: PeerReviewed
identifier:   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.  ISSN 22129820     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016434935&doi=10.1016%2fj.jcou.2017.03.011&partnerID=40&md5=d7123aac407012796927e1e5ca6fc010
relation: 10.1016/j.jcou.2017.03.011
identifier: 10.1016/j.jcou.2017.03.011