%0 Journal Article
%@ 17505836
%A Gonfa, G.
%A Bustam, M.A.
%A Shariff, A.M.
%D 2016
%F scholars:7016
%I Elsevier Ltd
%J International Journal of Greenhouse Gas Control
%K Absorption; Amines; Corrosion; Degradation; Desorption; Fossil fuels; Fuel storage; Gas emissions; Linear regression; Molecular graphics; Quantum chemistry, Amine-based chemical absorptions; Carbon dioxide absorption; COSMO-RS; Degradation by-products; Multiple linear regressions; QSPR; Quantitative structure activity relationship; Quantitative structureproperty/activity relationships (QSPR/QSAR), Carbon dioxide, absorption; carbon dioxide; carbon sequestration; degradation; desorption; multiple regression; nitrogen compound; numerical model; quantum mechanics; solvent
%P 372-378
%R 10.1016/j.ijggc.2016.03.022
%T Quantum-chemical-based quantitative structure-activity relationships for estimation of CO2 absorption/desorption capacities of amine-based absorbents
%U https://khub.utp.edu.my/scholars/7016/
%V 49
%X The capture and storage of CO2 produced from the use of fossil fuels for power generation is a key technology to reduce green gas emissions. Aqueous amine-based chemical absorption is the most mature technology for acid gases capture of gas streams. However, this process generates additional costs, mostly from the regeneration energy required to release the carbon dioxide from the solvent. Moreover, the deployment of this technology for CO2 capture from power sources causes amine degradation, equipment corrosion and generation of volatile degradation by-products. Therefore, an intensive work is demanded to screen solvents to overcome these challenges. Previous studies have demonstrated evidence that some relationships exist between the structure of amines and their capability for carbon dioxide absorption. In this work, quantum chemical based Quantitative Structure-Property/Activity Relationship (QSPR/QSAR) models were developed for prediction CO2 absorption and desorption capacities of some amines. The quantum chemical based descriptors were generated using COSMO-RS model. Multiple linear regression (MLR) was used for the model development. The accuracies of the models were verified by different statistical tests. The Quantitative Structure-Property/Activity Relationship (QSPR/QSAR) models can reasonably predict the CO2 absorption and desorption capacities of the amines. © 2016 Elsevier Ltd.
%Z cited By 12