An effective approach for lowering CO₂ emissions from industrial processes is the absorption method of CO₂ capture. Because of the high energy required to break the bond of the carbamate ions during the stripping process, the intramolecular interaction (repulsive interaction) of N_carbamate-C_carbamate was discovered to be the main interaction. Therefore, the purpose of this study is to examine the amine-CO₂ bond strength for various carbamate molecules during the regeneration process using molecular dynamic modelling, as well as to explore the diffusion coefficient of various amines. The results of interaction intensity show that in comparison to other studied amines for inter – and intra-molecular interactions N, N, N′, N′-tetramethylpropane-1,3-diamine (TMPAD), N-dimethylcyclohexanamine (DMCA) and 4-diethylamino-2-butanol (DEAB) were easy to break. It shows that the TMPAD has the highest repulsive interaction; consequently, it needs the lowest energy to break the carbamate ion in the stripping process as compared to MEA. The order of regeneration energy required to break the bond for N_carbamate-C_carbamate in various selected amines from higher to lower is MEA > 2MAE > PZ > 2DMAE > 2EAE > AMP > 1DMA2P > MCA > DMCA > DEAB > TMPAD. The diffusion coefficient data for various blends reveal that the 2MAE-DEAB blend has the highest rate of diffusion when compared to other blends (2MAE-1DMA2P and 2MAE-TMPAD).

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.