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
dc.contributor.author | Adogbeji, Victor Omoefe | |
dc.contributor.author | Atofarati, Emmanuel O. | |
dc.contributor.author | Sharifpur, Mohsen | |
dc.contributor.author | Meyer, Joshua P. | |
dc.contributor.email | mohsen.sharifpur@up.ac.za | |
dc.date.accessioned | 2025-08-07T07:19:22Z | |
dc.date.available | 2025-08-07T07:19:22Z | |
dc.date.issued | 2025-07 | |
dc.description.abstract | Please read abstract in the article. | |
dc.description.department | Mechanical and Aeronautical Engineering | |
dc.description.librarian | hj2025 | |
dc.description.sdg | SDG-09: Industry, innovation and infrastructure | |
dc.description.sponsorship | Open access funding provided by University of Pretoria. | |
dc.description.uri | https://link.springer.com/journal/10973 | |
dc.identifier.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. | |
dc.identifier.issn | 1388-6150 (print) | |
dc.identifier.issn | 1588-2926 (online) | |
dc.identifier.other | 10.1007/s10973-025-14399-y | |
dc.identifier.uri | http://hdl.handle.net/2263/103814 | |
dc.language.iso | en | |
dc.publisher | Springer | |
dc.rights | © The Author(s) 2025. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License. | |
dc.subject | Magnetic hybrid ferrofluids (MHFs) | |
dc.subject | Thermoelectric conductivity (TEC) | |
dc.subject | Stability | |
dc.subject | Hybridization mixing ratios | |
dc.subject | Viscosity | |
dc.subject | Heat transfer efficiency | |
dc.title | 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 | |
dc.type | Article |