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Ionic Clusters vs. Shear Viscosity in Aqueous Amino Acid Ionic Liquids

Aqueous solutions of amino acid ionic liquids (AAILs) are of high importance for applications in protein synthesis and solubilization, enzymatic reactions, templates for synthetic study, etc. This work employs molecular dynamics simulations using our own force field to investigate shear viscosity and cluster compositions of three 1-ethyl-3-methylimidazolium (emim) amino acid salts: [emim][ala], [emim][met], and [emim][trp] solutions (2, 5, 10, 20, 30 mol%) in water at 310 K. We, for the first time, establish simple correlations between cluster composition, on one side, and viscosity, on another side. We argue that knowledge about any of these properties alone is enough to derive insights regarding the missed properties, using the reported correlations. The numerical observations and qualitative correlations are discussed in the context of chemical structure of the amino acid anions, [ala], [met], and [trp]. The reported results will enhance progress in the efficient design and applications of AAILs and their solutions.

Additionally, AAILs are interesting as chiral solvents and reactants to dissolve and stabilize biomolecules, such as cellulose, nucleic acids, carbohydrates and other species of primary biological importance. 29 The presence of certain amounts of water is implied in all these applications, as water is omnipresent in living systems. The potential use of AAILs can only be fully realized when the detailed atomistic-precision information about physical chemical properties, structures and interactions in their condensed phase becomes available. 4,16,[30][31][32][33] Apart from the microscopic structures of pure AAILs, behavior of these liquids in aqueous medium is of undoubted interest. In particular, the extent of miscibility of AAILs and water are important for many practical applications. We consider AAILs based on 1-ethyl-3-methylimidazolium cation (emim). The established correlations allow to efficiently predict transport properties based on structure data, and contrariwise.

Simulation Details
Classical molecular dynamics (MD) simulations using conventional additive interaction potentials were performed employing our own force field (FF) for AAILs. TIP3P model of water was used to provide internal compatibility. 34 Figure 1). These particular AAILs were selected due to possessing significantly different amino acid residues. Indeed, alanine is a small molecule, which is largely hydrophilic. We expect perfect miscibility of [emim][ala] with water. In turn, methionine is more hydrophobic, while possessing sulfur. The sulfur atom is spatially separated from the hydrophilic moiety by the two methylene groups. Tryptophan is a relatively large molecule, which possesses two fused aromatic rings. Although five-membered ring contains a nitrogen atom, it does not alter a hydrophobic nature of the entire radical. All introduced anions were obtained by deprotonating carboxyl groups of the respective amino acid. The list of the simulated systems is provided in Table 1.  The Cartesian coordinates were saved every 1.0 ps for future processing in accordance with relationships of statistical physics. More frequent saving of trajectory components was preliminarily tested, but no systematic accuracy improvement was found. The first 10 ns of the simulation were regarded as equilibration. The subsequent 100 ns of the simulation were used for structure analysis. All systems were simulated in the constant-pressure constant-temperature ensemble, which allows attaining a natural mass density of each model system. The equations of motion were propagated with a time-step of 2.0 fs. Such a relatively large time-step was possible due to constraints imposed on the carbon-hydrogen covalent bonds (instead of a harmonic potential). Note, the time-step of 2.0 fs is more than ten times smaller than the period of the fastest harmonic bond oscillation in any of these systems.
The electrostatic interactions were simulated using direct Coulomb law up to 1.2 nm of separation between each pair of interaction sites. The electrostatic interactions beyond 1.2 nm were accounted for by computationally efficient Particle-Mesh-Ewald (PME) method. 36 It is important to use the PME method in the case of ionic systems, since electrostatic energy beyond the cut-off usually contributes 40-60% of the total electrostatic energy. The Lennard-Jones-12-6 interactions were smoothly brought down to zero from 1.1 to 1.2 nm using the classical shifted force technique. 37 The constant temperature, 310 K, was maintained by the Bussi-Donadio-Parrinello velocity rescaling thermostat (with a time constant of 0.1 ps), which provides a correct velocity distribution for a statistical mechanical ensemble. 38 The constant pressure was maintained by Parrinello-Rahman barostat with a time constant of 1.0 ps and a compressibility constant of 4.5×10 -5 bar -1 . 39 The compressibility constant only determines a genuine rigidity of the barostat. It should not be numerically equal to physical compressibility of the substance to obtain a correct system density.
All molecular dynamics trajectories were propagated using the GROMACS simulation engine. 37 Analysis of structure properties was performed using the supplementary utilities distributed with the GROMACS simulation suite, where applicable. The AAILs and water were placed in cubic periodic MD boxes (Figure 1), whose initial densities were calculated to approximately correspond to ambient pressure at 310 K.
Shear viscosity of each of 15 systems was calculated from non-equilibrium MD simulations with cosine-type acceleration. 40 The subsequent energy dissipation is used to assess system viscosity. The mathematical foundations of this method are provided elsewhere. 40,41 Ionic clusters are defined using the single-linkage approach with a cut-off distance of 0.3 nm. 37 The coordination center of cation was chosen to be most electron deficient imidazole hydrogen atom. The coordination center of anion was chosen to be deprotonated carboxyl group.
These selections were inspired by electronic structure calculations of the AAIL ion pairs in vacuum. 35 Any selected coordination center, located closer than 0.3 nm from the existing cluster, is considered to belong to the cluster.

Results and Discussion
Ionic structure of the AAIL solutions is characterized by means of ionic clusters formed by cations and anions together. An ion belongs to a given cluster when it exhibits at least one direct contact with any of the ions of this cluster. We select the two major descriptors: (1) the percentage of ions, which belong to ion pairs (as opposed to single ions and larger ionic clusters) and (2) the average size of the largest ionic cluster in the system. Note that the largest ionic cluster must be significantly smaller than the total number of ions in the system. Otherwise, AAIL engenders a separate phase (solid or liquid one) within water indicating limited solubility of ions. Figure Table 2 describe the fitting procedures and the corresponding parameters.
The percentage of ion pairs decreases as the first-order polynomial with respect to the logarithm of shear viscosity (Figure 4). In turn, viscosity increases exponentially with the molar content of AAIL. Table 2 shows that in the limit of small viscosity (A 0 parameter), the expected percentage of ion pairs in all AAILs is similar, 52.48-54.71%. The correlation coefficient, R 2 , is reasonably high ( Table 2) for this number of plotted data amounting to 0.96-0.97. The slope parameter (A 1 ) is negative (i.e. higher viscosity means less ion pairs) and increases as the size of the anion increases.