Abstract
The results of experimental (conductometry, NMR-diffusometry) and computational (MD simulations) studies on the binary mixtures of room-temperature imidazolium- and pyridinium-based ionic liquids (RTILs) with acetonitrile (AN), γ-butyrolactone (γ-BL) and propylene carbonate (PC) over the wide composition range are presented. The conductometric analysis was carried out in the RTILS mole fraction (χ(RTIL),) range between 0.0 and 0.5 in the temperature ranges from 278.15 to 328.15 K. Notably, all binary systems exhibit conductivity maximum at, χ(RTIL), between 0.1 and 0.2. This maximum slightly shifts towards smaller χ(RTIL), as counter-ion gets larger. Self-diffusion coefficients of solvent molecules and cations were obtained by means of 1H-NMR-diffusometry in mixtures of 1-n-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide tetrafluoroborate, trifluoromethanesulfonate and hexafluorophosphate with PC, γ-BL and AN over the whole concentration range at 300 K. The relative diffusion coefficients of solvent molecules to cations as a function of composition were established to be depended on a solvent but not on the anion of RTIL. In all cases the relative diffusion coefficients demonstrate a plateau at χ(RTIL) < 0.2 and then increase significantly for AN, moderately for γ-BL or negligibly for PC at higher RTIL content. Such behavior was attributed to the different solvation ability of the investigated solvents. In the mixtures with [BMIM][PF6] anion diffusion coefficients derived from 31P NMR were found to be higher than the corresponding values for cation in RTIL-depleted systems and lower in the RTIL-enriched systems. The inversion of relative ion diffusion is observed near the equimolar composition and being insensitive to the solvent. At this point a remarkable change in the diffusion mechanism of ion of RTIL is expected. Additionally, molecular dynamics simulations on the binary mixtures of 1-ethyl-3-methylimidazolium and 1-butyl-3-methylimidazolium tetrafluoroborates with AN were performed. The conductivity correlates with a composition of ion aggregates simplifying its predictability. Large amounts of AN stabilize ion pairs, although destroy greater ion aggregates. Based on the simulation results, we show that conductivity of the studied mixtures significantly depend on the ion aggregation.
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