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A study of changes in the heat capacity of carbon nanotube-based ionanofluids prepared from a series of imidazolium ionic liquids.
Parmar, Nirmal; Bendová, Magdalena; Wagner, Zdenek; Jacquemin, Johan.
Afiliação
  • Parmar N; Department of Chemistry and Physics of Aerosols, Institute of Chemical Process Fundamentals of the CAS, 16502, Prague 6, Czech Republic. parmar@icpf.cas.cz.
  • Bendová M; Department of Chemistry and Physics of Aerosols, Institute of Chemical Process Fundamentals of the CAS, 16502, Prague 6, Czech Republic. parmar@icpf.cas.cz.
  • Wagner Z; Department of Chemistry and Physics of Aerosols, Institute of Chemical Process Fundamentals of the CAS, 16502, Prague 6, Czech Republic. parmar@icpf.cas.cz.
  • Jacquemin J; Materials Science and Nano-Engineering, Mohammed VI Polytechnic University, 43150, Ben Guerir, Morocco.
Phys Chem Chem Phys ; 24(36): 22181-22190, 2022 Sep 21.
Article em En | MEDLINE | ID: mdl-36093723
ABSTRACT
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.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Phys Chem Chem Phys Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Phys Chem Chem Phys Ano de publicação: 2022 Tipo de documento: Article