Morphology-enhanced conductivity in dry ionic liquids
A Erbasa and MO de la Cruz, PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 18, 6441-6450 (2016).
Ionic liquids exhibit fascinating nanoscale morphological phases and are promising materials for energy storage applications. Liquid crystalline order emerges in ionic liquids with specific chemical structures. Here, we investigate the phase behaviour and related ionic conductivities of dry ionic liquids, using extensive molecular dynamics simulations. Temperature dependence, properties of polymeric tail and excluded volume symmetry of the amphiphilic ionic liquid molecules are investigated in large scale systems with both short and long-range Coulomb interactions. Our results suggest that by adjusting stiffness and steric interactions of the amphiphilic molecules, lamellar or 3D continuous phases result in these molecular salts. The resulting phases are composed of ion rich and ion pure domains. In 3D phases, ion rich clusters form ionic channels and have significant effects on the conductive properties of the observed nano-phases. If there is no excluded-volume asymmetry along the molecules, mostly lamellar phases with anisotropic conductivities emerge. If the steric interactions become asymmetric, lamellar phases are replaced by complex 3D continuous phases. Within the temperature ranges for which morphological phases are observed, conductivities exhibit low-temperature maxima in accord with experiments on ionic liquid crystals. Stiffer molecules increase the high-conductivity interval and strengthen temperature-resistance of morphological phases. Increasing the steric interactions of cation leads to higher conductivities. Moreover, at low monomeric volume fractions and at low temperatures, cavities are observed in the nano-phases of flexible ionic liquids. We also demonstrate that, in the absence of electrostatic interactions, the morphology is distorted. Our findings inspire new design principles for room temperature ionic liquids and help explain previously-reported experimental data.
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