Designing ionic liquid solvents for carbon capture using property-based visual approach

Recently, ionic liquids (ILs) have been introduced as potential carbon dioxide (CO₂)-capturing solvents, as a substitute to conventional amine-based solvents. Conventional amine-based solvents that are used for CO₂ capture show some drawbacks, such as high solvent loss, high regeneration energy requirement, and solvent degradation. These shortcomings can be potentially overcome if IL-based solvents are considered. ILs have negligible vapour pressure, high thermal stability, and wide range of thermophysical properties. Nonetheless, using experimentation to identify suitable ILs as CO₂-capturing solvents is a tedious and costly task, as there are more than a million possible combinations of cations and anions that make up the ILs. Computer-aided tools have been previously developed for targeted IL design, which often involve non-linear programming. However, non-linear programming sometimes fails to converge, due to enlarged search space for optimal solution and its complex formulations. In this paper, the authors present a simple yet systematic visual approach to design IL solvents for carbon capture. Property integration framework is employed in this approach to systematically design IL, where the design problem can be mapped from the property domain into a cluster domain through clustering technique. The advantage of the visual approach is the ability to enumerate novel IL candidates. Group contribution (GC) method is included in the framework to estimate the properties of designed ILs. By combining property integration framework and GC method, the proposed approach is able to provide a property-based platform to visualise the performance of designed ILs on a ternary diagram. A case study is presented to illustrate the validity of the proposed approach.