Computational study of CO2 solubility in amino acid-based ionic liquids using COSMO-RS

Abstract

Abstract. The carbon capture, use, and sequestration (CCUS) techniques are proven to be efficient at lowering the atmospheric concentration of carbon dioxide. Notwithstanding the advances in this area, there are still significant restrictions in carbon dioxide (CO2) capture techniques in industry such as high capital costs, solvent evaporation losses, and low absorption and desorption rates. Ionic liquids (ILs) have received much interest as green solvent due to the benefits of their distinctive properties such as low vapor pressure and their capacity to capture CO2 making them a suitable replacement for present solvents, such as amines. Amino acid based ILs having close similarity with the alkanolamines may potentially have high affinity for CO2 absorption. Nevertheless, available database on these ILs is still limited and only focus on the common types of amino acids. Therefore, this paper aims to predict the CO2 absorption of different amino acid-based ionic liquids as cation/anion using quantum chemical calculation tools namely Conductor like Screening Model for Real Solvents (COSMO-RS) and TURBOMOLE. We evaluated 84 different ILs of different cations and anions based on their CO2 capacity, activity coefficient at infinite dilution (γ∞), and Henry’s constant (H). The results showed that amino acid as anions significantly enhanced the CO2 solubility compared to amino acid as cations. However, glycinium tetrafluoroborate [Gly+][BF4] showed high affinity for CO2 absorption compared to other amino acid-cations based with activity coefficient at infinite dilution (γ∞) = 0.117 and (H) = 8.07. We showed that the selection of anions/cations can significantly change the CO2 capacity in ILs.