Statistical Analysis of Thermal Conductivity Experimentally Measured in Water-Based Nanofluids

TL;DR

This paper conducts a statistical analysis of experimental data on water-based nanofluids' thermal conductivity, revealing influences of concentration, temperature, and particle size, but highlights data scatter limits definitive conclusions.

Contribution

It provides a comprehensive statistical correlation analysis of existing experimental data on nanofluids' thermal conductivity, identifying key influencing factors and data limitations.

Findings

Conductivity increases with particle concentration and temperature.

Silica nanofluids show size-dependent heat transfer effects.

High data scatter limits definitive conclusions.

Abstract

Nanofluids are suspensions of nanoparticles in a base heat-transfer liquid. They have been widely investigated to boost heat transfer since they were proposed in the 1990's. We present a statistical correlation analysis of experimentally measured thermal conductivity of water-based nanofluids available in the literature. The influences of particle concentration, particle size, temperature and surfactants are investigated. For specific materials (alumina, titania, copper oxide, copper, silica and silicon carbide), separate analyses are performed. The conductivity increases with the concentration in qualitative agreement with Maxwell's theory of homogeneous media. The conductivity also increases with the temperature (in addition to the improvement due to the increased conductivity with water). Surprisingly, only silica nanofluids exhibit a statistically significant effect of particle size, whereby smaller particles lead to faster heat transfer. Overall, the large scatter in the experimental data prevents a compelling, unambiguous assessment of these effects. Taken together, the results of our analysis suggest that more comprehensive experimental characterizations of nanofluids are necessary to estimate their practical potential.