Document type
Journal articles
Document subtype
Full paper
Title
Thermal Conductivity of Ionic Liquids and IoNanofluids. Can Molecular Theory Help?
Participants in the publication
Xavier Paredes (Author)
Dep. Química e Bioquímica
CQE
Maria José Lourenço (Author)
Dep. Química e Bioquímica
CQE
Carlos Nieto de Castro (Author)
Dep. Química e Bioquímica
CQE
William Wakeham (Author)
IMPERIAL COLLEGE LONDON
Summary
Ionic liquids have been suggested as new engineering fluids, specifically in the area of\\\\nheat transfer, and as alternatives to current biphenyl and diphenyl oxide, alkylated aromatics and\\\\ndimethyl polysiloxane oils, which degrade above 200 ?C, posing some environmental problems.\\\\nAddition of nanoparticles to produce stable dispersions/gels of ionic liquids has proved to increase\\\\nthe thermal conductivity of the base ionic liquid, potentially contributing to better efficiency of heat\\\\ntransfer fluids. It is the purpose of this paper to analyze the prediction and estimation of the thermal\\\\nconductivity of ionic liquids and IoNanofluids as a function of temperature, using the molecular\\\\ntheory of Bridgman and estimation methods previously developed for the base fluid. In addition,\\\\nwe consider methods that emphasize the importance of the interfacial area IL-NM in modelling the\\\\nthermal conductivity enhancement. Results obtained show that it is not currently possible to predict\\\\nor estimate the thermal conductivity of ionic liquids with an uncertainty commensurate with the\\\\nbest experimental values. The models of Maxwell and Hamilton are not capable of estimating the\\\\nthermal conductivity enhancement of IoNanofluids, and it is clear that the Murshed, Leong and Yang\\\\nmodel is not practical, if no additional information, either using imaging techniques at nanoscale or\\\\nmolecular dynamics simulations, is available.
Date of Publication
2021-03-12
Institution
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Where published
Fluids
Publication Identifiers
Publisher
MDPI AG
Document Identifiers
DOI -
https://doi.org/10.3390/fluids6030116
URL -
https://doi.org/10.3390/fluids6030116
URL -
https://www.mdpi.com/2311-5521/6/3/116
Rankings
SCIMAGO Q2 (2022) - 0.399 - Chemical Engineering
Keywords
IoNanofluids
nanofluids
molecular theory
prediction
estimation
thermal conductivity
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