Analyzing the experimental data of CO2 equilibrium absorption in the aqueous solution of DEAÂ +Â MDEA with Random Forest and Leverage method

The continuing production of energy from fossil fuels is responsible for large emissions of CO2 component of greenhouse gases. Employing amine-based solutions is a common approach for removing the produced CO2 in numerous carbon capture systems. In this communication, a novel methodology namely Random Forest (RF) is employed for developing a tree-based predictive tool. The prediction capability of the proposed RF model is compared to the modified Deshmukh-Mather thermodynamic model. The presented RF model shows an average absolute relative deviation percent (AARD%) of 3.74, while the modified Deshmukh-Mather model estimates the CO2 loading capacity of the DEA + MDEA solution with AARD% of 12.10. Furthermore, the reliability and quality of the experimental data for CO2 solubility in DEA + MDEA aqueous solution has been investigated in this study using Leverage algorithm. According to the results, there are two probable doubtful data points in the investigated database.