Abstract
Room-temperature ionic liquids (RTILs) stand out among molecular liquids for their rich physicochemical characteristics, including structural and dynamic heterogeneity. The significance of electrostatic interactions in RTILs results in long characteristic length- and timescales, and has motivated the development of a number of coarse-grained (CG) simulation models. In this study, we aim to better understand the connection between certain CG parameterization strategies and the dynamical properties and transferability of the resulting models. We systematically compare five CG models: a model largely parameterized from experimental thermodynamic observables; a refinement of this model to increase its structural accuracy; and three models that reproduce a given set of structural distribution functions by construction, with varying intramolecular parameterizations and reference temperatures. All five CG models display limited structural transferability over temperature, and also result in various effective dynamical speedup factors, relative to a reference atomistic model. On the other hand, the structure-based CG models tend to result in more consistent cation–anion relative diffusion than the thermodynamic-based models, for a single thermodynamic state point. By linking short- and long-timescale dynamical behaviors, we demonstrate that the varying dynamical properties of the different CG models can be largely collapsed onto a single curve, which provides evidence for a route to constructing dynamically-consistent CG models of RTILs.
Highlights
Of the broad variety of molecular liquids, ionic liquids (ILs) stand out for their rich physicochemical characteristics [1, 2]
By linking short- and long-timescale dynamical behaviors, we demonstrate that the varying dynamical properties of the different CG models can be largely collapsed onto a single curve, which provides evidence for a route to constructing dynamically-consistent CG models of Room-temperature ionic liquids (RTILs)
Note that if the model derived from this method fails to reproduce the target vector of the equations, i.e., bAA, it implies that the cross-correlation matrix generated by the higher resolution model does not accurately represent the correlations that would be generated by the resulting CG model
Summary
Of the broad variety of molecular liquids, ionic liquids (ILs) stand out for their rich physicochemical characteristics [1, 2]. ILs are salts, with a melting point or glass-transition temperature that can reach low temperatures—notably, ‘roomtemperature’ ionic liquids (RTILs) are in the liquid state at ambient conditions. RTILs are commonly composed of an organic cation and an inorganic anion. ILs play an important role as a solvent in sustainable chemistry, with applications including biomaterials and catalysis [3,4,5,6]. ILs are strong candidates in electrochemical applications. The amphiphilic nature of these cations facilitates the formation of nanoscale segregation. Nanoscale segregation increases when the temperature is decreased toward the glass transition, evidenced by shifts in the static structure factor [10]. Low temperatures can yield specific dynamical effects, such as a breakdown of the Stokes–Einstein–Debye relation [14]. Despite a wealth of studies characterizing the properties of ILs, a clear link between the structural and dynamical properties of these systems, especially close to the glassy regime, remains elusive
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