Abstract
Ionic liquids have been suggested as new engineering fluids, specifically in the area of heat transfer, and as alternatives to current biphenyl and diphenyl oxide, alkylated aromatics and dimethyl polysiloxane oils, which degrade above 200 °C, posing some environmental problems. Addition of nanoparticles to produce stable dispersions/gels of ionic liquids has proved to increase the thermal conductivity of the base ionic liquid, potentially contributing to better efficiency of heat transfer fluids. It is the purpose of this paper to analyze the prediction and estimation of the thermal conductivity of ionic liquids and IoNanofluids as a function of temperature, using the molecular theory of Bridgman and estimation methods previously developed for the base fluid. In addition, we consider methods that emphasize the importance of the interfacial area IL-NM in modelling the thermal conductivity enhancement. Results obtained show that it is not currently possible to predict or estimate the thermal conductivity of ionic liquids with an uncertainty commensurate with the best experimental values. The models of Maxwell and Hamilton are not capable of estimating the thermal conductivity enhancement of IoNanofluids, and it is clear that the Murshed, Leong and Yang model is not practical, if no additional information, either using imaging techniques at nanoscale or molecular dynamics simulations, is available.
Highlights
Ionic liquids appeared in the last two decades as one of the most promising categories of fluids for chemistry, chemical engineering, and medical applications
Results we examine the performance of the schemes proposed for the estimation of the thermal conductivity of nanofluids and IoNanofluids
We examine the performance of the schemes proposed for the estimation of the thermal conductivity of nanofluids and IoNanofluids
Summary
Ionic liquids appeared in the last two decades as one of the most promising categories of fluids for chemistry, chemical engineering, and medical applications. Like extraction, separation, fluid movement, heat and mass transfer and reaction engineering, the properties of ionic liquids and of their mixtures with molecular and associating solvents are needed to design and operate the chemical plants. Being “target oriented” or “duty oriented” materials, the evaluation of their properties needs experimental measurements (very limited and time consuming), but theoretical developments and computer simulation, in order to develop sustainable and useful tools for project design, which we have carried through for molecular liquids These arguments pave the way to predictive/estimation methods, a fundamental tool to be developed and incorporated in process design simulators. The term prediction has been widely used in the past to name methodologies that have totally different levels of theoretical or empirical support, while estimation is used indiscriminately for purely based empirical schemes and for methods with some theoretical insight
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