McCabe, Clare M. Vanderbilt University
Ionic liquids (ILs) are liquids, comprised entirely of complex ions, that typically have melting points at or below room temperature, distinguishing them from high temperature molten salts (e.g., NaCl). The cations and anions each impart different physical and chemical properties to the IL enabling ILs to be tailored to provide desired properties. While initial interest in ILs focused on their use as solvents, it has since broadened dramatically with ILs finding applications from catalysis, separations, sensors, solar cells, batteries, thermal fluids and lubricants. These applications, combined with the number of possible ILs being estimated to be in the billions, underlines the need to develop an accurate tool to design task-specific ILs.
Despite increased experimental studies and physical property investigations, it is currently not possible to predict which ion combinations will lead to a desired set of properties. The limited progress to date in IL design has been achieved primarily through experimentation in chemical composition leading to empirical heuristics relating chemistry to properties.
Despite its obvious utility, a predictive design methodology for ILs, based upon a deep physical understanding of the structure and interactions within ILs, does not exist today. This is in part because ILs and their mixtures with other molecular species are exceptionally complex systems and present particularly difficult molecular modeling challenges, both from simulation and theory points of view, especially if we wish to be able to predict IL properties in the absence of experimental data. We will address this need through the development of a molecular-based theoretical framework with which to study the thermodynamic properties of ILs. The approach developed will be akin to the models used in molecular simulation studies and will enable the prediction of IL properties from the chemical composition, so eliminating empiricism in estimating the properties of a given combination of ions and their mixtures with molecular species. In addition to enabling product design for ILs and their mixtures, the proposed methodology will be a crucial component in the design of chemical processes involving ILs.
Ionic liquids (ILs) are liquids, comprised entirely of complex ions, that typically have melting points at or below room temperature, distinguishing them from high temperature molten salts (e.g., NaCl). As a results ILs and their mixtures with other molecular species are exceptionally complex systems and present particularly difficult molecular modeling challenges, both from simulation and theory points of view. We are addressing this need through the development of a molecular-based theoretical framework with which to study the thermodynamic properties of charged fluids. Specifically we have developed an equation of state that can accurately model the thermodynamic properties of charged fluids with a minimum of reliance on experimental data. We have also developed parameters for additional functional groups that will allow us in ongoing work to merge the theoretical developments for charged fluids with the group-contribution based equation of state that the PI has developed. Charged fluids are important to a wide range of systems from natural biological processes to industrial chemical processes such as osmosis and reverse osmosis, fertilizer production, water purification, geochemistry, electrochemistry, and enhanced oil recovery. The ubiquitous presence of charged fluids makes the development of accurate equations of state for their thermodynamic study a important area of research. The project has trained two graduate students and an undergraduate student in molecular modeling and process simulation. The students have gained significant teaching and mentoring experience through their interaction with undergraduate students working in the lab and participation in CyberCamp. CyberCamp, co-organized by the PI, is an annual hands-on intensive cybercamp on molecular modeling methods attended by undergraduate and graduate students working on various experimental and simulation projects. About one quarter of the cybercamp participants are typically undergraduates performing computational research as part of Vanderbilt summer research programs or NSF-funded REU programs on campus. The PI presents lectures on process modelling and SAFT using results from this project as examples.
