A study of changes in the heat capacity of carbon nanotube-based ionanofluids prepared from a series of imidazolium ionic liquids

Ionanofluids (INFs), nanoparticles dispersed into a base fluid, e.g. an ionic liquid, are a novel class of alternative heat transfer fluids. Addition of nanoparticles to a base ionic liquid is the prime reason for an enhancement in the thermophysical properties of ionanofluids. However, due to very...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Physical chemistry chemical physics : PCCP Ročník 24; číslo 36; s. 22181
Hlavní autoři: Parmar, Nirmal, Bendová, Magdalena, Wagner, Zdeněk, Jacquemin, Johan
Médium: Journal Article
Jazyk:angličtina
Vydáno: 21.09.2022
ISSN:1463-9084, 1463-9084
On-line přístup:Zjistit podrobnosti o přístupu
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Ionanofluids (INFs), nanoparticles dispersed into a base fluid, e.g. an ionic liquid, are a novel class of alternative heat transfer fluids. Addition of nanoparticles to a base ionic liquid is the prime reason for an enhancement in the thermophysical properties of ionanofluids. However, due to very limited research on ionanofluids, further studies are required to understand changes in the isobaric heat capacity of ionanofluids as a function of size of cations of the base ionic liquid structure and concentration of nanoparticles. Herein, isobaric heat capacity was measured as a function of temperature for the prepared ionanofluid samples from a series of imidazolium ionic liquids and multi walled carbon nanotubes (MWCNTs). Moreover, the influence of the size of cations on the isobaric heat capacity enhancement mechanism and the stability of ionanofluid samples was studied. Furthermore, experimental isobaric heat capacity data were assessed by a novel non-statistical data analysis method named mathematical gnostics (MG). MG marginal analysis was used to evaluate the most probable values from the measured data set. A robust linear regression along a gnostic influence function was also used to find the best fit to correlate the measured data.Ionanofluids (INFs), nanoparticles dispersed into a base fluid, e.g. an ionic liquid, are a novel class of alternative heat transfer fluids. Addition of nanoparticles to a base ionic liquid is the prime reason for an enhancement in the thermophysical properties of ionanofluids. However, due to very limited research on ionanofluids, further studies are required to understand changes in the isobaric heat capacity of ionanofluids as a function of size of cations of the base ionic liquid structure and concentration of nanoparticles. Herein, isobaric heat capacity was measured as a function of temperature for the prepared ionanofluid samples from a series of imidazolium ionic liquids and multi walled carbon nanotubes (MWCNTs). Moreover, the influence of the size of cations on the isobaric heat capacity enhancement mechanism and the stability of ionanofluid samples was studied. Furthermore, experimental isobaric heat capacity data were assessed by a novel non-statistical data analysis method named mathematical gnostics (MG). MG marginal analysis was used to evaluate the most probable values from the measured data set. A robust linear regression along a gnostic influence function was also used to find the best fit to correlate the measured data.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1463-9084
1463-9084
DOI:10.1039/d2cp02110b