Thermal Conductivity Calculations for Nanoparticles Embedded in a Base Fluid

Abstract

The Prasher analytical model was used for calculating the thermal conductivity of the embedded nanoparticles of Al2O3, CuO, ZnO, and SiO2 in conventional fluids, such as water and ethylene glycol. The values that were obtained were used in the nanofluid theoretical models for comparison with experimental data, where good agreement was obtained. Liang and Li’s theoretical model was also used to calculate the thermal conductivity of these nanoparticles, where the results agreed with those obtained using the Prasher model. The effect of the liquid nanolayer thickness around the nanoparticles that was used to enhance the effective thermal conductivity of nanofluids was explained. The role of the nanoparticles’ surface specularity parameter, which was size-dependent, was clarified. This theoretical trend provides a simple method for estimating the thermal conductivity of nanoparticles and nanofluids.

Reviewing thermal conductivity aspects of solar salt energy storage

“…Although some calculations using theoretical models have been done, as discussed, the experimental results are very different due to different BFs, with a large difference in thermal conductivity results. 107 However, it is clear that the addition of nanoparticles elevates thermal conductivity and this elevation depends on the quantity of nanoparticles added.…”

Review on grain size effects on thermal conductivity in ZnO thermoelectric materials

“…Evans and co-workers concluded that the thermal conductivity of nanouids was described by the effective medium theory, with the aggregation of the particles causing an improvement in the thermal conductivity of nanouids. 94,95 However, Wu et al 96 found that the size of 100 nm at room temperature can result in a decrease in thermal conductivity of $50% compared to massive crystals. This was due to the lower thermal conductivity of ZnO, which resulted from the smaller phonon group velocities, the larger three-phonon scattering phase space, and the larger anharmonicity.…”

Can graphene improve the thermal conductivity of copper nanofluids?

“…Other factors, such as the preparation technique, stabilizing agents, air-exposure time, flow characteristics and acidity of the NF have also been described as relevant. 6,7,[14][15][16][17][18][19] For example, Bhanushali et al investigated how the shape of the NPs determines the k of water-based Cu NFs using distinct filler particles: short nanowires (mean diameter (D m ) = 26 nm; mean length (L m ) = 7.8 mm), long nanowires (D m = 26 nm; L m = 96 mm), nanospheres (D m = 48 nm), and nanocubes (D m = 87 nm). The NPs were treated with the same dispersant and antioxidant to exclude the potential effects of the surface-capping ligands.…”

“…To date, many efforts have been made to explain the mechanisms behind the k enhancement in NFs, through various methodologies and assumptions. 1,7,13,15,16,55 However, more studies are necessary to understand how each factor influences the structural, thermodynamic, reactive, and mechanical properties of the Cu@G NPs and to quantify their contribution to the improvement of the k of Cu@G-based NFs. In addition to the experimental techniques, high-performance computing-assisted materials design has proved to be a powerful tool for gathering insight from different physical phenomena.…”

“…Other factors, such as the preparation technique, stabilizing agents, air-exposure time, flow characteristics and acidity of the NF have also been described as relevant. 6,7,14–19…”