Comparison of Experimental Measurements of Thermal Conductivity of Fe2O3 Nanofluids Against Standard Theoretical Models and Artificial Neural Network Approach

In the present work, the practicability of Fe2O3 nanofluids for heat transfer applications has been examined. Nanofluids performance, in terms of modulation of thermal conductivity, has been investigated with increasing concentration of Fe2O3 nanoparticles in water and ethylene glycol base fluids at 10, 20, 30, 40, 50, 60 and 70 degrees C. Fe2O3 nanoparticles have been synthesized using the wet chemical method and characterized using TEM, SEM, XRD and UV-Vis. The characterization results revealed a face-centered cubic structure having alpha phase and particle size in the range of 40-55 nm for the synthesized Fe2O3 nanoparticles. Thermal conductivity measurement results show increases in thermal conductivity with the increase in concentration and temperature of nanofluids. 16.45 and 19.76% enhancement in thermal conductivity have been observed for Fe2O3-water and Fe2O3-ethylene glycol nanofluids of 2 vol.% at 70 degrees C compared to water and ethylene glycol base fluids at 10 degrees C, respectively. Results of the ANN approach are in good agreement with experimental results, and H-C model gives better predictions compared to other standard models. The study gives clear insights into improved heat transfer performance by material engineering.