Magnetic field induced augmented thermal conduction phenomenon in magneto-nanocolloids

Katiyar, Ajay; Dhar, Purbarun; Nandi, Tandra; Das, Sarit K.

doi:10.1016/j.jmmm.2016.06.065

Cited by 32 publications

(19 citation statements)

References 36 publications

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“…The predictions using the proposed model in this study show a better agreement with the experimental data than those of the theoretical model proposed in Ref. 35.…”

Section: Resultssupporting

confidence: 69%

“…ratio crosses the threshold value (a ¼ 1), and it ends when ferrofluid becomes saturated at a high magnetic field. 12 This trend is reflected in the experimental measurements 18,35 and the model presented in this study is able to not only predict the flattening at low and high values of the field, but also accurately capture the increasing trend. This is due to the hyperbolic tangent modeling [Eqs.…”

Section: Resultssupporting

confidence: 57%

“…The empirically found function can appropriately address the contribution of the factors that are difficult to be analytically taken into account such as the treatment method of the particles, polydispersity, and rheology of the matrix fluid. The model has been employed to predict the thermal conductivities of the Fe 3 O 4kerosene and Fe 3 O 4 -ethylene glycol ferrofluids using the experimental data taken from the two independent references.18, 35 The predictions have been found to be in a good agreement with experimental data showing that the proposed model can appropriately envisage the aggregation development and thereby the in-field thermal conductivity of ferrofluids.…”

Section: Discussionmentioning

confidence: 89%

“…3, the experimental data are in a reasonable agreement with the theoretical predictions by the proposed model. Similar procedures is followed to find the compression function for ferrofluids containing magnetite particles with an average size of 75 nm dispersed in ethylene glycol (EG) using the experimental set of data obtained by Katiar et al 35 Multiple data points corresponding to three concentration values have been employed as the training set to find compression function n. Thermal conductivities are then computed and plotted for all different concentration values ranging from 1% to 7% as seen in Fig. 4.…”

Section: Resultsmentioning

confidence: 99%

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Effective in-field thermal conductivity of ferrofluids

Mousavi

Kumar

2018

Journal of Applied Physics

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A structural model to predict in-field thermal conductivity of ferrofluids is proposed in this study and is validated by the experimental data from the literature. The model is able to capture the aggregation development of the magnetic particles with increasing magnetic field strength. Introducing a compression function that can be found empirically, the model can accurately predict the thermal conductivity, especially the plateauing at low and high magnetic fields.

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“…The predictions using the proposed model in this study show a better agreement with the experimental data than those of the theoretical model proposed in Ref. 35.…”

Section: Resultssupporting

confidence: 69%

Section: Resultssupporting

confidence: 57%

Section: Discussionmentioning

confidence: 89%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Effective in-field thermal conductivity of ferrofluids

Mousavi

Kumar

2018

Journal of Applied Physics

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“…Due to the formed heterogeneous structure in MNF, the thermal conductivity is anisotropic. It was found that the thermal conductivities parallel to the magnetic field direction are, in most cases, much higher than the perpendicular ones [21][22][23]. Thus, the magnetic field direction and distribution in the study of MNF thermal conductivity plays a key role.…”

Section: Introductionmentioning

confidence: 99%

Magnetic Field Effect on Thermal, Dielectric, and Viscous Properties of a Transformer Oil-Based Magnetic Nanofluid

Rajňák

Dolník

et al. 2019

Energies

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Progress in electrical engineering puts a greater demand on the cooling and insulating properties of liquid media, such as transformer oils. To enhance their performance, researchers develop various nanofluids based on transformer oils. In this study, we focus on novel commercial transformer oil and a magnetic nanofluid containing iron oxide nanoparticles. Three key properties are experimentally investigated in this paper. Thermal conductivity was studied by a transient plane source method dependent on the magnetic volume fraction and external magnetic field. It is shown that the classical effective medium theory, such as the Maxwell model, fails to explain the obtained results. We highlight the importance of the magnetic field distribution and the location of the thermal conductivity sensor in the analysis of the anisotropic thermal conductivity. Dielectric permittivity of the magnetic nanofluid, dependent on electric field frequency and magnetic volume fraction, was measured by an LCR meter. The measurements were carried out in thin sample cells yielding unusual magneto-dielectric anisotropy, which was dependent on the magnetic volume fraction. Finally, the viscosity of the studied magnetic fluid was experimentally studied by means of a rheometer with a magneto-rheological device. The measurements proved the magneto-viscous effect, which intensifies with increasing magnetic volume fraction.

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Nanofluids: Definition & Classification

Kumar

Subudhi

2021

Lecture Notes in Mechanical Engineering

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Magnetic field induced augmented thermal conduction phenomenon in magneto-nanocolloids

Cited by 32 publications

References 36 publications

Effective in-field thermal conductivity of ferrofluids

Effective in-field thermal conductivity of ferrofluids

Magnetic Field Effect on Thermal, Dielectric, and Viscous Properties of a Transformer Oil-Based Magnetic Nanofluid

Nanofluids: Definition & Classification

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