Modeling and prediction of carbon dioxide loading for amine solutions using structural parameters
Volume Title: 1
1Department of Chemical Engineering, Caspian Faculty of Engineering, College of Engineering, University of Tehran, Tehran, Iran
2انستیتو مهندسی نفت دانشگاه تهران
3Caspian faculty of engineering, College of engineering, University of Tehran, Rezvanshahr, Iran
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.