(159ac) Rapid Screening of Ionic Liquids and Deep Eutectic Solvents for CO2 Capture at Industrial Conditions– from Molecular-Level to Process Modeling.

The utilization of aqueous amines, chiefly monoethanolamine (MEA), has been the longstanding benchmark solvent for CO₂ capture. However, limitations of these solvents such as their energy intensive regeneration requirements, low chemical and thermal stability, and high solvent volatility, are major obstacles towards their industrial commercialization, directly linked to the solvent’s thermodynamic properties. This fueled the current progress in the development of task-designer solvents such as Ionic liquids (ILs) and Deep eutectic solvents (DESs), with their prime advantage being their tunability feature. The additional degree of freedom during solvent synthesis facilitates the selection of starting materials targeting specific properties attractive for CO₂ capture, such as high chemical and thermal stability, along with low solvent volatility. However, an additional level of complication is faced as the number of available ILs and DESs examined for CO₂ capture are quite extensive. Additionally, the criteria employed in ascertaining their potentiality for CO₂ capture remain limited in scope and scale, primarily focusing on CO₂ solubility measured at conditions representative of industrial scale applications. Aside from that, other thermophysical properties of relevance, such as enthalpy of absorption, and solvent viscosity are typically neglected.

Towards the proper assessment of the performance of these solvents at industrially representative conditions, a holistic examination of their relevant properties is essential. The integral element for such an examination is the development of paradigm that directly connects molecular level behavior of these solvents with their techno-economic feasibility at process level. In this contribution, we demonstrate the application of an integrated modeling approach, linking a robust molecular-based equation of state, namely, soft-SAFT EoS [1,2], with a detailed process modeling and economic analysis for ILs and DESs for CO₂ capture.

The thermophysical and transport properties of ILs, and DESs, and their performance as solvents for CO₂ capture were evaluated within the framework of the soft-SAFT EoS. This thermodynamic model is a coarse-grain approach, modeling fluids as chains of connected groups, characterized by a set of molecular parameters representing key structural and energetic features. The examined ILs were modeled as associating chainlike fluids [3], while DESs were as binary mixtures of their individual components, with each component being represented by separate set of molecular parameters [4,5]. CO₂ was modeled as a chain-like molecule, explicitly accounting for its quadrupole moment. The soft-SAFT EoS was employed in its full potential to obtain all relevant thermodynamic properties essential for process modeling. This is done in a systematic manner through modeling properties of pure ILs and DESs such as solvent density, viscosity (using free volume theory), and interfacial tension (using density gradient theory), along with assessing their CO₂ solubilities.

Once these solvents were fully characterized using available experimental data, the model was used in a predictive manner to assess the technical performance and economic feasibility of these solvents in a pressure-swing absorption (PSA) process. Particular attention was given to performance criteria such as absorption capacity, energy consumption, and economic indicators such as capital, operating costs, and total annualized costs. The solvent performance was evaluated taking into account a variety of operating conditions, and CO₂ feed conditions representative of post-combustion, and pre-combustion capture processes.

The current procedure established its efficacy in rapidly screening a large number of ILs and DESs, not only in terms of technical criteria, but also economic indicators at representative industrial conditions. This success stems from the application of a robust and accurate molecular model combined with macroscopic thermodynamics

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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