Carbon Nanotube-Based Ionanofluids for Efficient Energy Storage: Thermophysical Properties’ Determination and Advanced Data Analysis

Ionanofluids
(INFs), ionic liquids (ILs) containing dispersed nanoparticles,
show fascinating thermophysical properties. The amount of dispersed
nanoparticles influences the properties of the base IL, allowing for
a fine-tuning of the properties of the resulting INF. Even though
INFs have been studied for more than a decade now, sufficient and
reliable data are still lacking. The aim of this work is to report
on the heat capacity, viscosity, melting temperature, and electrical
conductivity of INFs based on 1-ethyl-3-methylimidazolium bis­(trifluoromethylsulfonyl)­imide
as a function of multi-wall carbon nanotube compositions. In this
work, mathematical gnostics has been also used to estimate the uncertainty
in each measured property. Moreover, a robust linear regression along
a gnostic influence function was used to find the best curve fit for
the measured data.