Uncovering molecular secrets of ionic liquids

1 Introduction

Ionic liquids offer high-potential solutions to an amazingly broad range of applications. The large number of cations and anions which can be combined to a low melting salt suggests the feasibility to design a required liquid for every task. The variety of possible ionic liquids even outnumbers traditional solvents in chemistry. Unfortunately, little is known about general properties of ionic liquids except the obvious fact that they consist solely of ions. It is the human and scientific nature that always finds its way to characterize the unknown or find ways to overcome challenges. One such challenge is the distillation of ionic liquids which was originally thought impossible due to the low volatility of known ionic liquids. However, ionic liquids can be distilled.

The history of ionic liquids goes back nearly one hundred years. As early as 1914, Paul Walden reported the first systematic study of ionic liquids. However, the scope of ionic liquids was recognized barely until the development of air and water stable imidazolium-based ionic liquids in 1992. Since then, the interest in these compounds has increased greatly leading to manifold applications of these compounds in natural sciences and industry. For example, ionic liquids are used in battery, solar cell, fuel cell, and lubricant applications. Nevertheless, even fundamental properties of ionic liquids are far from being understood.

Due to the technical progress and the developments in theoretical chemistry over the last 20 years, computational methods have become a powerful tool in chemistry because various approaches can be employed for an investigation at the molecular scale. Observed macroscopic properties can be assigned to functional parts of a molecule which facilitates a more task-related design of new compounds. Still, the interplay of nuclei and electrons is too complex for feasible black box methods of systems larger than a few atoms. Therefore, a computational chemist should always choose an approach carefully and verify how the necessary approximations influence the results.

Ionic liquids are a special challenge for computational chemistry. Due to the important role of cooperativity, the investigation of large systems is necessary to obtain reliable results. Unfortunately, only for medium sized systems are there any computational approaches available which possess the required flexibility of electronic structure for an accurate ab initio description of cooperativity. Additionally, not only cooperativity, but also dispersion forces make the choice of a reliable approach for ionic liquids a challenging task. Nevertheless, carefully selected computational approaches allow predictions for ionic liquids, which can be confirmed by experiments if possible. One example is the nanoscale segregation of polar and nonpolar domains (also called microheterogeneity) in ionic liquids. These domains were found in corse-grained model and in fully atomistic model molecular dynamics simulations before they were reported by X-ray diffraction or Raman-induced Kerr effect spectroscopy studies as well. Not only the prediction of the liquid structure but also the calculation of thermodynamic data, like the gaseous enthalpy of formation, is feasible. These two discussed examples exemplify that carefully selected computational approaches are a powerful tool for the investigation of ionic liquids.

2 Choice of a suited computational method

The investigation of large systems is necessary for ionic liquids due to the important role of cooperativity. Additionally, commonly used ionic liquids consist of inorganic anions and organic cations with alkyl side chains and aromatic moieties. Both functional groups of the cation are well-known for a significant contribution of dispersion forces to equilibrium structure and interaction energy. Long alkyl chains of ionic liquids result in nanoscale segregation, in which the nonpolar domains are dominated by dispersion forces. Furthermore, π-π-stacking of aromatic cations was also observed. Even the interplay of counter ions is influenced significantly by dispersion forces. Thus, reliable computational approaches for an investigation of ionic liquids do not need only a proper description of electrostatic and induction forces, also an accurate description of dispersion forces is needed.

Ab initio correlated or so-called post Hartree–Fock methods provide a proper description of dispersion forces. Unfortunately, these methods are computationally limited to systems with few atoms. Only few CCSD(T) calculations of very small ionic liquid systems were reported so far. Second-order Møller–Plesset perturbation theory (MP2) might be also a suitable ab initio method to study ionic liquids. Recent developments have made this approach available for systems with hundreds of atoms. However, calculations of medium sized ionic liquid systems need still enormous computational resources. Thus, MP2 and similar approaches seem to be limited to static quantum chemical calculations and are still too expensive for ab initio molecular dynamics simulations over an appropriate system size and time frame.

A feasible compromise of accurate forces and available system size might be Kohn–Sham density functional theory (KS-DFT). Several approaches, especially for general gradient approximation (GGA) functionals, are known to reduce the computational cost much lower than for conventional correlation methods. Unfortunately, KS-DFT accounts for electrostatic, exchange and induction forces very well, but fails for the description of dispersion forces. Del Pópolo et al. have attributed observed large errors in calculated equilibrium volumes of ionic liquid crystal structures to the limitations of KS-DFT in dealing with dispersion interactions. Several possible solutions were proposed to correct this shortcoming of Kohn–Sham density functional theory. Most computational investigations of ionic liquids still use traditional exchange-correlation functionals, e.g. B3LYP, without a dispersion correction. However, two studies have shown that energy and structure obtained with traditional functionals deviates to MP2 references similar like Hartree-Fock calculations. Zahn and Kirchner reported that the empirical dispersion correction proposed by Grimme in 2006 reduces the deviation to the reference values significantly. An empirical dispersion correction by a dispersion corrected atom-center dispersion potential...