Experimental investigation and machine learning modeling of the effects of hybridization mixing ratio nanoparticle type and temperature on the thermophysical properties of Fe3O4TiO2 Fe3O4MgO and Fe3O4ZnODI water hybrid ferrofluids

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dc.article.end-page10573en
dc.article.start-page10549en
dc.citation.doi10.1007/S10973-025-14399-Yen
dc.contributor.authorVictor O Adogbejien
dc.contributor.authorEO Atofaratien
dc.contributor.authorMohsen Sharifpuren
dc.contributor.authorJP Meyeren
dc.date.accessioned2025-08-26T09:26:43Z
dc.facultyFACULTY OF ENGINEERING & THE BUILT ENVIRONMENTen
dc.identifier.citationWOSen
dc.identifier.issn1388-6150en
dc.identifier.urihttps://hdl.handle.net/10539/46057
dc.journal.titleExperimental investigation and machine learning modeling of the effects of hybridization mixing ratio nanoparticle type and temperature on the thermophysical properties of Fe3O4TiO2 Fe3O4MgO and Fe3O4ZnODI water hybrid ferrofluidsen
dc.journal.volume150en
dc.titleExperimental investigation and machine learning modeling of the effects of hybridization mixing ratio nanoparticle type and temperature on the thermophysical properties of Fe3O4TiO2 Fe3O4MgO and Fe3O4ZnODI water hybrid ferrofluidsen
dc.typeJournal Articleen

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