A thermodynamic framework for determination of gas hydrate stability conditions and water activity in ionic liquid aqueous solution

The formation of gas hydrates in pipelines and plugging of the gas flow path are a major cause of operating expenses, safety issues, pressure drop, and fatal accidents. Therefore, the inhibition of gas hydrate formation is of paramount importance. The utilization of a new class of inhibitors such as ionic liquids (ILs) is currently of great interest. In this regard, adjusting water activity in the inhibitor blend (water + IL) is a vital factor. Several models have been developed to calculate the activity of water in the presence of IL(s). The major disadvantage of these models is their correlative basis. This study aimed to propose a rigorous predictive model for the calculation of water activity in the presence of IL(s), which would then be applied in the prediction of the gas hydrate stability conditions. The model is made up of a molecular term (the short-range interactions from Free-Volume-Flory-Huggins (FVFH) activity model) as well as a contribution from ionic interactions as a result of IL(s) dissociation in water (the long-range electrostatic interactions from the extended Debye-Huckel (EDH) model). The overall absolute temperature deviation and the average absolute relative deviation percent in the calculated gas (methane and carbon dioxide) hydrate dissociation temperatures for the whole databank (500 data points including 37 ILs) were found to be 0.61 K and 0.22%, respectively. This proves the superiority of the model over the previous correlative-basis ones. Finally, it is concluded that the higher temperature, the higher the IL(s) concentration, and the lower IL(s) molecular weight(s) result in larger model deviations. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

A rigorous predictive model for calculating water activity in the presence of ionic liquids (ILs) is proposed and applied in the prediction of gas hydrate stability conditions. The model accounts for both short-range interactions and long-range electrostatic interactions and has been validated with data, demonstrating its superiority.