Impact of nanoconfinement on the physical state and conductivity mechanisms of a 2-picolinium ionic liquid crystal

Abstract

Hybrid solid-like materials prepared from the incorporation of liquid-like ionic conductors into nanoporous matrices could represent an advantage for a variety of electronic applications. Aiming to obtain such materials, three composites of the polymorphic ionic liquid crystal (ILC) 1-hexadecyl-2-methylpyridinium bromide ([C16-2-Pic][Br]), loaded in the mesoporous inorganic silica SBA-15 (∼6.8 nm in pore diameter), were prepared at guest–host weight fractions of ∼ 40, 60 and 80% (w/w) and investigated by different techniques: ATR-FTIR, BET, TGA, XRD and DSC. Complete amorphisation was achieved for the 40 and 60% composites, while the 80% preparation was stabilised in the low-T morph of native C16, being in the liquid state at room temperature. Furthermore, through Dielectric Relaxation Spectroscopy, the ionic conductivity of the three hybrid materials was characterised, allowing to deconvolute this property in a pure ohmic contribution (conductivity I) and the overlapping of ac − dc transition with interfacial polarisation resulting from the coexistence of the ionic liquid and the quasi-insulating inorganic matrix (conductivity II). From –20 to 20 °C, the conductivity and the corresponding charge migration are faster in all composites relative to the neat ILC, as deduced from the inferior radii of Nyquist arcs. The 60% preparation stood out from the other materials, exhibiting direct conductivity unaffected by electrode polarisation over a larger T-range, leading to the assumption of a nearly continuous silica-mediated charge migration pathway, which is never reached for the 40% composite, while, in the 80% preparation, some C16 deposits on the outer surface of the pores. Incorporation into the silica matrix proved to be a good strategy for the production of cost-efficient materials with long-term stabilisation of the ionic liquid in a single phase over a large range of temperatures, enabling the prediction of flow and conductive properties.