Computational Investigation of Co-Solvent Influence on CO2 Absorption and Diffusion in Water Lean Solvents

Abstract

The present research explores water-lean amine-based solvents to enhance carbon capture and provide sustainable solutions for CO2 emissions challenges. A computational approach is employed to evaluate the co-solvent’s impact on CO2 capture in MDEA-based systems. The performance of the following systems is examined: MDEA-NMP, MDEA-MAE-NMP, MDEA-MeOH, MDEA-MAE-MeOH, MDEA-EG, MDEA-MAE-EG, and MDEA-MAE with varying water concentrations. The Radial Distribution Function (RDF) analysis revealed significant interactions between amine groups, CO2, and water molecules in each system. The results indicate that the MDEA-NMP (40% H2O) and MDEA-EG (40% H2O) systems had strong interactions, indicating their potential for CO2 capture. However, adding MAE decreased interaction intensities, indicating a less favorable performance. Complementing the RDF findings, the Mean Square Displacement (MSD) analysis quantified CO2 diffusivity across temperatures (313 K, 323 K, and 333 K). MDEA-NMP (40% H2O) demonstrated the highest diffusivity, indicating superior CO2 mobility and capture efficiency. MDEA-MeOH (40% H2O) also showed moderate diffusivity, further supporting its effectiveness. However, solvent systems incorporating MAE consistently displayed lower diffusivity, reinforcing the observation from the RDF analysis. The temperature effect on the diffusivity of selected blends does not follow the regular pattern in a co-solvent-based system, whereas in an aqueous system, it increases with temperature. These molecular dynamic simulations highlight the critical role of solvent composition in optimizing CO2 capture efficiency. Applying these insights can improve solvent formulations, enhance effectiveness, and reduce costs.