Molecular Origins of the Thermophysical Properties of Ionic Liquids in External Electric Fields

Advancements in chemical separation processes are essential to sustainably meet the growing demand for electronics. In particular, solvent design under external stimuli requires progress. Ionic liquids (ILs) offer an opportunity to investigate how external electric fields (EEFs) affect separation media. Their low volatility, high thermal stability, and tunable thermophysical properties make ILs attractive for sustainable separations. Moreover, their charged nature makes them ideal for probing the direct effects of EEFs on nanoscale dynamics and structure, which can in turn influence macroscopic properties. This dissertation establishes structure–property relationships for ILs under EEFs using molecular dynamics (MD) simulations. It demonstrates and quantifies for ILs electrostriction—the contraction or expansion of an IL under an applied field—for the first time. By linking the charge density and ion size of IL constituents to the electrostrictive coefficient, it provides new physical insights into IL molecular properties. Further, the molecular origins of IL thermophysical behavior in EEFs are explored by testing excess entropy scaling relationships. These relationships directly connect liquid structure to dynamic properties across multiple temperatures and field strengths, enabling predictions of how EEF-induced structural changes drive observed transport phenomena. The impact of EEFs on the glass transition temperature (Tg) of ILs is also investigated. An automated, objective MD-based method computes Tg and reveals that fields above a critical strength depress Tg during cooling. Analysis of liquid-phase dynamics and structure indicates that EEFs lower the activation energy for diffusion, reducing the energetic barrier for molecular motion and consequently lowering Tg. This effect is leveraged to propose an electrified non-vapor-compression refrigeration cycle. Finally, the dissertation develops a general automated approach for predicting Tg from MD simulations, offering a robust tool for materials design under external stimuli.