The viscosity of dilute carbon nanotube (1D) and graphene oxide (2D) nanofluids
Resumen: Controlling the physicochemical properties of nanoparticles in fluids directly impacts on their liquid phase processing and applications in nanofluidics, thermal engineering, biomedicine and printed electronics. In this work, the temperature dependent viscosity of various aqueous nanofluids containing carbon nanotubes (CNTs) or graphene oxide (GO), i.e. 1D and 2D nanoparticles with extreme aspect ratios, is analyzed by empirical and predictive physical models. The focus is to understand how the nanoparticle shape, concentration, motion degrees and surface chemistry affect the viscosity of diluted dispersions. To this end, experimental results from capillary viscosimeters are first examined in terms of the energy of viscous flow and the maximum packing fraction applying the Maron–Pierce model. Next, a comparison of the experimental data with predictive physical models is carried out in terms of nanoparticle characteristics that affect the viscosity of the fluid, mostly their aspect ratio. The analysis of intrinsic viscosity data leads to a general understanding of motion modes for carbon nanoparticles, including those with extreme aspect ratios, in a flowing liquid. The resulting universal curve might be extended to the prediction of the viscosity for any kind of 1D and 2D nanoparticles in dilute suspensions.
Idioma: Inglés
DOI: 10.1039/D0CP00468E
Año: 2020
Publicado en: PHYSICAL CHEMISTRY CHEMICAL PHYSICS 22, 20 (2020), 11474-11484
ISSN: 1463-9076

Factor impacto JCR: 3.676 (2020)
Categ. JCR: PHYSICS, ATOMIC, MOLECULAR & CHEMICAL rank: 8 / 37 = 0.216 (2020) - Q1 - T1
Categ. JCR: CHEMISTRY, PHYSICAL rank: 77 / 162 = 0.475 (2020) - Q2 - T2

Factor impacto SCIMAGO: 1.052 - Physics and Astronomy (miscellaneous) (Q1) - Physical and Theoretical Chemistry (Q1)

Financiación: info:eu-repo/grantAgreement/ES/DGA/T03-20R
Financiación: info:eu-repo/grantAgreement/ES/MICINN/Juan de la Cierva Program-IJCI-2016-27789
Financiación: info:eu-repo/grantAgreement/ES/MINECO/BES-2014-068727
Financiación: info:eu-repo/grantAgreement/ES/MINECO-FEDER/ENE2016-79282-C5-1-R
Tipo y forma: Article (Published version)
Área (Departamento): Área Ciencia Comput.Intelig.Ar (Dpto. Informát.Ingenie.Sistms.)
Exportado de SIDERAL (2022-11-24-09:14:17)


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articulos > articulos-por-area > cc_de_la_computacion_e_inteligencia_artificial



 Notice créée le 2022-11-24, modifiée le 2022-11-24


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