(445a) Rational Design of Aqueous Ionic Liquids for Biogas Upgrading Using a Molecular-Based Equation of State

Over the past decades, the potentiality of task-specific solvents, such as ionic liquids (ILs) and deep eutectic solvents (DESs), for carbon dioxide (CO₂) capture and separation, with the potential of replacing conventional aqueous amines [1]. Their attractiveness for biogas upgrading is due to their high CO₂ uptake, and easily tunable and unique thermophysical properties such as low volatility and high thermal and chemical stability compared to aqueous amines [2,3]. Notwithstanding, a primary issue with the application of ILs for CO₂ separation is their high viscosity, which has an adverse effect on the mass transfer between CO₂ and the solvent, directly affecting the capital and operating costs of the process [4]. Mixtures of ILs with other physical solvents such as water or alcohols have the potential to effectively reduce the viscosity of these solvents, however, this would be on the expense of reducing their CO₂ capturing ability [5]. This would require fine-tuning the ratio of both solvents, taking into account the inherent trade-off between CO₂ uptake, viscosity, and other criteria such as absorption selectivity, and regeneration energy requirements. Accomplishing such a task using experimental techniques, considering the large number of available ILs and their possible hybrid mixtures with physical solvents is time and cost intensive. However, with the current advancements in computational power and molecular modeling approaches, the accomplishment of such as task is made easier, allowing the systematic evaluation of the effect of the addition of a physical solvent on the performance of ILs for a particular application.

In this contribution, we demonstrate the application of a robust molecular-based equation of state (EoS), namely, soft-SAFT EoS [6,7], towards the rational design of aqueous ionic liquids for biogas upgrading. The thermodynamic modeling of pure fluids within the framework of soft-SAFT is done in a coarse-grain manner by representing fluids by a set of molecular parameters characterizing key structural and energetic features. The examined ILs, [C₄mim][BF₄], [C₄mim][PF₆], [C₂mim][NTf₂], and [C₂mim][CF₃SO₃], were modelled as associating chainlike fluids [8] , CO₂ was modelled as a chainlike molecule with explicit consideration of its quadrupolar nature [9], hydrogen sulfide (H₂S) was modelled as an associating fluid, methane (CH₄) was modelled as a non-associating, non-polar spherical segment, while water was modelled as an associating spherical segment [10,11]. The thermodynamic modeling was done in a systematic manner initially through validating the performance of the thermodynamic model with available experimental data [5,12,13]. This examination included solubility of CO₂, H₂S, and CH₄ in pure ILs and pure water, phase equilibria and viscosity of binary mixtures of ILs and water, solubility of the aforementioned gases in aqueous ILs. The assured reliability of the thermodynamic model permitted the predictive application of the model in a systematic examination of the effect of water content in aqueous ILs on their performance for biogas upgrading. This was inclusive of a wide range or properties such as solvent viscosity, solubility of CO₂, CH₄, and H₂S, along with absorption selectivity, and lastly enthalpy of CO₂ absorption.

With these criteria, the water content in aqueous ILs was optimized to ensure the maximum gain from the inherent trade-off with the addition of water to ILs in terms of reduced CO₂ solubility, and reduced solvent viscosity.

This framework with a molecular-based EoS at its center attests to the efficacy of employing molecular modeling approaches to the rational design of solvents for CO₂ capture and separation, that assists in a more targeted deployment of experimental efforts on promising solvents.

This work is funded by Khalifa University of Science and Technology (RC2-2019-007). Computational resources from the Research and Innovation Center on CO₂ and H₂ (RICH Center) are gratefully acknowledged.

References

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