**Author details**

models consisting of Bingham Plastic model and Power Law model as shown in **Figure 11** respectively. In **Figure 11**, it was observed 25 ppm concentration of graphene oxide dispersed yields the lowest shear stress while 50 ppm has the highest shear stress values at higher shear rates. A plausible explanation to this anomaly could be the increased stacking of graphene oxide sheets trapped due to the spindle's rotating movement. Comparisons have shown Bingham model gave better predictions of graphene oxide-hydrogenated oil-based nanofluids compared to Power Law model. The Power Law model over-predicted the shear stress values at higher shear rate due to the flow behaviour index at *n* > 1. Furthermore, hydrogenated oil-based nanofluid has comparatively similar yield stress values at different concentrations at higher temperatures. The rheological behaviour of hydrogenated oil-based nanofluids approaches a limit in which the shear stress values are independent to the concen-

From the experimental analysis, hydrogenated oil-based fluid exhibits a non-Newtonian behaviour. Although the fluid exhibited zero shear stress at low temperature, the decreased in viscosity of hydrogenated oil-based fluid exhibited shear-thinning properties. However, the flocculation structure of nanoparticles was broken apart to form primary particle which led to slight shear thickening behaviour at higher shear rates. Similar to other findings, higher concentration of nanoparticles exhibits higher viscosity and shear stress properties but variations are insignificant upon comparison. Furthermore, the shear stress values are independent to the concentration of nanoparticles dispersed at higher temperature. The comparison between Bingham model and Power Law model showed Bingham model predicting better results data as compared to Power Law model at all concentrations, nanoparticle types and

In this study, graphene oxide-hydrogenated oil nanofluids were homogenized through combination of hydrodynamic cavitation and ultrasonication combination process at 25 ppm, 50 ppm and 100 ppm respectively. FTIR analysis had shown presence of large –OH groups concentration while TEM analysis shows severe defects and bends attributed to attachments of various groups on the surface. Findings have shown addition of graphene oxide into hydrogenated oil showed remarkable improvements of 12.00% in thermal conductivity enhancement at 100 ppm and 50°C. Furthermore, the rheological properties of hydrogenated oil nanofluid showed no significant changes in rheological behaviour when compared against the base fluid. Hydrogenated oil-based nanofluids have shown to possess both shear thinning and shear thickening behaviours at lower shear rates approaching higher shear rate range with increased viscosity at higher nanoparticle concentrations. Conventional thermal conductivity models were able to predict graphene oxide-based nanofluids accurately at higher particle concentration while Bingham Plastic model had shown to fit well against experimental data at all concentrations and temperature, thus proving addition of graphene oxide does not

tration of nanoparticles at high temperature [55].

change the intrinsic behaviour of hydrogenated oil.

temperature.

80 Drilling

**6. Conclusion**

Yee Ho Chai1 , Suzana Yusup1 \*, Vui Soon Chok<sup>2</sup> and Sonny Irawan<sup>3</sup>

\*Address all correspondence to: drsuzana\_yusuf@utp.edu.my

1 Chemical Engineering Department, Biomass Processing Laboratory, Centre for Biofuel and Biochemical Research, Institute for Sustainable Living, Universiti Teknologi PETRONAS, Perak, Malaysia

2 KL-Kepong Oleomas Sdn. Bhd, Selangor, Malaysia

3 Petroleum Engineering Department, Universiti Teknologi PETRONAS, Perak, Malaysia
