Prediction of CO2 loading of amines in carbon capture process using membrane contactors: A molecular modeling

Abstract

Separation of carbon dioxide from gas streams with respect to CO2 negative environmental effects is one of the most significant parts of gas separation processes. For this purpose, using membrane contactors is a promising technology and finding high performance solvents is crucial to development of this technology. Aqueous solutions of amines are the most employed solvents for this aim. The fact that performance of amines in carbon capture is greatly affected by variation in their molecular structure has been proven. Quantitative structure property relationship (QSPR) is a technique which employs molecular structure related variables known as descriptor for modeling. In this paper, QSPR method is employed for modeling and predicting CO2 loading of different amines after absorption and desorption steps in carbon removal process using membrane contactors. Physico-chemical and theoretical descriptors were calculated for a data set including sixteen amines. Variable selection and model development were performed by genetic algorithm-multiple linear regression (GA-MLR) method. Developed models could predict CO2 loading of amines’ solutions after absorption and desorption by coefficient of determination of 0.986 and 0.989 and standard error of the estimate equal to 0.0572 and 0.0496, respectively. In comparison between desorption and absorption model, desorption model is more accurate and absorption model provides simpler descriptors. Validity of the developed models were confirmed by different statistical tests and models showed high predictability power. Furthermore, mechanistic interpretation was applied in order to explain the relation between CO2 loading and descriptors which appeared in the models. It was found out that steric hindrance effect has a more significant influence on desorption than absorption.