A data-driven optimization approach for the molecular design of CO2 capture ionic liquids mixtures Academic Article in Scopus uri icon

abstract

  • CO (Formula presented.) emissions into the atmosphere have become a global concern in recent years. The amount of CO (Formula presented.) generated in post-combustion processes has attracted the attention of the international scientific community. Some processes use alkanolamines to absorb CO (Formula presented.); however, their volatility increases the process cost. An alternative to this limitation is the use of ionic liquids (ILs) as solvents in the CO (Formula presented.) absorption process. An important characteristic of ILs is their extremely low vapour pressure, making them practically non-volatile. In this work, molecular dynamics simulation (MDS) was employed to calculate the absorption capacity of an IL mixture, and a design of experiments approach guided by Bayesian optimization (BO) was used to find an optimal IL mixture that maximizes the amount of CO (Formula presented.) captured. The applied methodology helps to reduce the number of numerical experiments and, consequently, computation time. The IL mixture analyzed was [BMIM][NTF (Formula presented.)] (Formula presented.) and [EMIM][SCN] (Formula presented.) (1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide and 1-ethyl-3-methylimidazolium thiocyanate) due to their known effectiveness as absorbents. With only 12 simulations, the composition of the IL mixture that achieve maximum CO (Formula presented.) absorption was determined. The results obtained encourage further exploration of other IL mixtures that may absorb greater amounts of CO (Formula presented.). © 2025 Canadian Society for Chemical Engineering.

publication date

  • January 1, 2026