Experimental investigation and machine learning modeling of the effects of hybridization mixing ratio, nanoparticle type, and temperature on the thermophysical properties of Fe3O4/TiO2, Fe3O4/MgO, and Fe3O4/ZnO-DI water hybrid ferrofluids
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Springer
Abstract
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Magnetic hybrid ferrofluids (MHFs), Thermoelectric conductivity (TEC), Stability, Hybridization mixing ratios, Viscosity, Heat transfer efficiency
Sustainable Development Goals
SDG-09: Industry, innovation and infrastructure
Citation
Adogbeji, V.O., Atofarati, E.O., Sharifpur, M. et al. Experimental investigation and machine learning modeling of the effects of hybridization mixing ratio, nanoparticle type, and temperature on the thermophysical properties of Fe3O4/TiO2, Fe3O4/MgO, and Fe3O4/ZnO-DI water hybrid ferrofluids. Journal of Thermal Analysis and Calorimetry 150, 10549–10573 (2025). https://doi.org/10.1007/s10973-025-14399-y.