62nd Annual Report on Research 2017

This project is focused on the use of ionic liquid and ionic liquid blends as replacement solvents for extraction processes using a combination of molecular simulation and thermodynamic modeling. There are a large number of ionic liquids that have previously been synthesized, and an even larger number of potential ionic liquids and ionic liquid mixtures. The use of molecular simulation alone would be impracticable. A central feature of this work is on the development of thermodynamic models to guide molecular simulations. Specifically, we are working to extend the model MOSCED to ionic liquids and their mixtures. The use of MOSCED is advantageous because it can not only be used to predict limiting activity coefficients, but it can additionally give insight into the underlying phase behavior. The work of the past year has focused on three areas involving MOSCED.

MOSCED to predict phase-equilbria

MOSCED takes the general form:

where is the limiting activity coefficient of the solute (2) in a solvent (1), and the first three terms result from comparing solute and solvent intermolecular interactions. A limitation of MOSCED is it can only predict limiting activity coefficients. In order to predict composition dependent activity coefficients which may be necessary for phase-equilibria calculations, MOSCED must be used to parameterize an excess Gibbs free energy model. In this study, we assessed the ability of MOSCED to predict composition dependent activity coefficients by predicting binary isobaric azeotropic vapor-liquid equilibrium and binary liquid-liquid equilibrium (or mutual solubilities). The excellent performance achieved for these highly non-ideal systems is encouraging as we move on to complex ionic liquids.

MOSCED to model a solute in a multi-component solvent

As written in equation (1), MOSCED is applicable for a solute in a solvent. As we ultimately desire to model solutes in ionic liquid mixtures, we desire to extend MOSCED to multicomponent solvents. One way to accomplish this is to use MOSCED to predict limiting activity activity coefficients for each binary pair making up the solution, and using this to parameterize an excess Gibbs free energy model. Unfortunately, we lose the physical insight of MOSCED when looking at solvent mixtures. We found that we could extend MOSCED to a solute in multicomponent solvent by using volume fraction average solvent MOSCED parameters. This allowed us to compute the limiting activity coefficient of the solute as a function of the solvent composition. The methodology was verified by using MOSCED to predict solubility in binary solvents. As a consequence of our mean solvent parameters, we were able to develop MOSCED based rules for how to select solvents to achieve solubility enhancement, which results when a solute is more comfortable in a solvent mixture as compared to any of the pure solvents.

Predicting MOSCED parameters

A limitation of MOSCED is that parameters need to be available for a solute/solvent pair in order to make predictions. Currently, MOSCED is parameterized for 130 organic solvents and water. We therefore developed a group contribution method to predict MOSCED parameters. As we seek to study solutes in ionic liquid and mixtures of ionic liquids with conventional solvents, this will allow us to obtain accurate parameters for missing species.

The proposed method works well to predict parameters of organic solvents and relatively small solid solutes. However, parameters are missing for large, multi-functional solid solutes. We have therefore investigated the use of molecular simulation and electronic structure calculations in the SMD and SM8 continuum solvent models to predict MOSCED parameters. Specifically, both molecular simulation and electronic structure calculations may be used to generate a set of reference solvation free energies, which may then be used to regress MOSCED parameters. As compared to using molecular simulation or electronic structure calculations alone, by parameterizing MOSCED, predictions may be made in additional solvents, in solvent mixtures, and at additional temperatures. Between this and our group contribution method, we are confident that we can obtain accurate parameters for any solute and organic solvent that we may encounter.

Impact

After the first year, we are well poised to accomplish the goals of the proposal. In the second year we will move on to parameterize MOSCED for ionic liquids, and to use this to identify systems to study using detailed molecular simulations.

Three undergraduate students were primarily supported by this PRF grant in the first 2016-2017 grant year, which encompassed Winter and Summer 2017, and one additional undergraduate student worked on this project supported by the Undergraduate Summer Scholars Program from the Miami University Office of Undergraduate Research with additional support from the Miami University College of Engineering and Computing. Students were paid during break times (Winter and Summer), and earned academic credit during the academic year for their work. An additional two undergraduates worked on the project solely during the academic year for credit. The experience afforded the students the opportunity to use state-of-the-art computational methods and additionally to use a physical based model for process design applications. Additionally, the students have had the opportunity to write-up research articles with the guidance of the PI, and to additionally present their work as poster and oral presentations at professional meetings. Based on his work, one of these students placed second in the paper competition at the AIChE North Central Student Regional Conference. Of the undergraduate students who worked on the project, three have graduated. Two of these students will continue to work on the project in the combined BS/MS program at Miami, where they will be supported next year by the grant as MS students. Without financial support to stay at Miami, graduate studies may not have been an option to them.

The results of this project have been disseminated through presentations at regional and national meetings. Both the PI and students have presented at meetings including the Ohio Supercomputing Center Statewide User Group bi-annual conference, the Midwest Thermodynamics and Statistical Mechanics Conference, the American Institute of Chemical Engineers (AIChE) Annual Meeting, and the AIChE North Central Student Regional Conference.