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
Victor O. Adogbeji, Emmanuel O. Atofarati, Mohsen Sharifpur, Josua P. Meyer
Abstract
Abstract This study experimentally investigates the influence of hybridization mixing ratio (HMR), nanoparticle size, and temperature on the stability, thermal conductivity, viscosity, and thermoelectric conductivity of $${\text{Fe}}_{3}{\text{O}}_{4}/$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mtext>Fe</mml:mtext> <mml:mn>3</mml:mn> </mml:msub> <mml:msub> <mml:mtext>O</mml:mtext> <mml:mn>4</mml:mn> </mml:msub> <mml:mo>/</mml:mo> </mml:mrow> </mml:math> Ti $${\text{O}}_{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mtext>O</mml:mtext> <mml:mn>2</mml:mn> </mml:msub> </mml:math> -DIW, $${\text{Fe}}_{3}{\text{O}}_{4}/$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mtext>Fe</mml:mtext> <mml:mn>3</mml:mn> </mml:msub> <mml:msub> <mml:mtext>O</mml:mtext> <mml:mn>4</mml:mn> </mml:msub> <mml:mo>/</mml:mo> </mml:mrow> </mml:math> MgO-DIW, and $${\text{Fe}}_{3}{\text{O}}_{4}/$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mtext>Fe</mml:mtext> <mml:mn>3</mml:mn> </mml:msub> <mml:msub> <mml:mtext>O</mml:mtext> <mml:mn>4</mml:mn> </mml:msub> <mml:mo>/</mml:mo> </mml:mrow> </mml:math> ZnO-DIW magnetic hybrid ferrofluids (MHFs). A two-step preparation technique was used to synthesize 0.3% volume concentration of the MHFs at HMRs of 80:20, 60:40, and 40:60, respectively. The study’s result revealed that the thermal and electrical conductivity of the MHF was proportional to the temperature of the MHF. Also, the viscosity and thermoelectric conductivity (TEC) of the MHF was inversely related to the MHF’s temperature. The (80:20) ratio consistently stands out for superior stability and thermal conductivity. An exceptional electrical conductivity of 4.23 mS/cm was displayed by the $${\text{Fe}}_{3}{\text{O}}_{4}/$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mtext>Fe</mml:mtext> <mml:mn>3</mml:mn> </mml:msub> <mml:msub> <mml:mtext>O</mml:mtext> <mml:mn>4</mml:mn> </mml:msub> <mml:mo>/</mml:mo> </mml:mrow> </mml:math> Ti $${\text{O}}_{2}(18\text{ nm})$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mtext>O</mml:mtext> <mml:mn>2</mml:mn> </mml:msub> <mml:mrow> <mml:mo>(</mml:mo> <mml:mn>18</mml:mn> <mml:mspace/> <mml:mtext>nm</mml:mtext> <mml:mo>)</mml:mo> </mml:mrow> </mml:mrow> </mml:math> -DIW at 50 °C. The best thermal conductivity–viscosity balance was observed for the $${\text{Fe}}_{3}{\text{O}}_{4}/$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mtext>Fe</mml:mtext> <mml:mn>3</mml:mn> </mml:msub> <mml:msub> <mml:mtext>O</mml:mtext> <mml:mn>4</mml:mn> </mml:msub> <mml:mo>/</mml:mo> </mml:mrow> </mml:math> ZnO-DIW with HMR of 80:20 at 50 °C as it has the highest thermal conductivity enhancement of 31.28% and the least viscosity. These findings guide MHF customization, emphasizing stability and thermophysical performance balance. $${\text{Fe}}_{3}{\text{O}}_{4}/$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mtext>Fe</mml:mtext> <mml:mn>3</mml:mn> </mml:msub> <mml:msub> <mml:mtext>O</mml:mtext> <mml:mn>4</mml:mn> </mml:msub> <mml:mo>/</mml:mo> </mml:mrow> </mml:math> ZnO-DI also had the best TEC value, making it most suitable for cooling PEM fuel cells. Linear regression analysis was used to generate the thermal conductivity correlations for the MHFs, while feature importance analysis highlights temperature as the most significant variable influencing their thermal conductivity.