Modeling and Prediction of Carbon Dioxide Loading For Amine Solutions Using Structural Parameters

Global warming is a huge concern all over the world, which is mostly caused by growing concentrations of co2 and other greenhouse gases in the atmosphere# many technologies offer a variety of methods to reduce carbon dioxide emissions to the atmosphere based on regenerable amine-based solvents# given that, testing on a large number of amines is not economically and time feasible# therefore, finding the primary structural characteristics of amine solutions and their effects on absorption values are very remarkable# quantitative structure-property relationship (qspr) presents an effective method for the prediction of co2 absorption by amine solutions# in this work, the qspr method was employed on a group of amine solutions, including ring-shaped structures# for the construction of the linear model, ga-mlr (genetic algorithm-multi linear regression) approach was applied# the value of the square of correlation coefficient (r2) for the linear model was 0#895# the attained model was then assessed by different statistical analyses# according to the results, the presented model is suitable, precise, and efficient for the prediction of absorption values# another conclusion that could be drawn is that the prediction of absorption values is achievable with high accuracy and power of predictability#