Rate-Based Process Optimization and Sensitivity Analysis for Ionic-Liquid-Based Post-Combustion Carbon Capture

Ionic liquids (ILs) are a promising class of absorbents for next-generation carbon-capture processes. In particular, aprotic heterocyclic anion ILs (AHAs) have received significant attention due to their ability to chemically absorb CO2 without a significant increase in viscosity. The development of process modeling and mathematical optimization approaches for AHA-based carbon-capture processes is essential for the evaluation of economic feasibility before industrial implementation. In this paper, we use a pseudo-transient modeling approach that enables the robust simulation and optimization of the large-scale process flowsheet. A Langmuir-type model that incorporates both the chemical and physical uptake of CO2 is used to describe the equilibrium absorption of CO2 by the IL. A rigorous rate-based model for the absorption column is employed to account for the effect of reversible chemical reactions on mass transfer. The models are then used to carry out economic optimization of a prototypical IL-based carbon-capture process. A sensitivity analysis of important IL properties is provided, revealing the key factors that affect IL choice. Finally, a comparison to an advanced amine-based process is briefly discussed.