Muhammad Ilman Hakimi Chua Abdullah

Effect of hexagonal boron nitride nanoparticles as an additive on the extreme pressure properties of engine oil

Purpose This paper aims to investigate the effect of hexagonal boron nitride (hBN) nanoparticles on extreme pressure (EP) properties when used as an additive in lubricating oil. Design/methodology/approach The nano-oil was prepared by dispersing an optimal composition of 0.5 vol. per cent of 70 nm hBN in SAE 15W-40 diesel engine oil using a sonication technique. The tribological testing was performed using a four-ball tribometer according to the ASTM standard. Findings It was found that the nano-oil has a potential to decelerate the seizure point on the contact surfaces, where higher EP can be obtained. More adhesive wear was observed on the worn surfaces of ball bearing lubricated with SAE 15W-40 diesel engine oil as compared with the nano-oil lubrication. Originality/value The results of the experimental studies demonstrated the potential of hBN as an additive for improving the load-carrying ability of lubricating oil.

Improving Engine Oil Properties by Dispersion of hBN/Al2O3 Nanoparticles

This paper provides oil properties study of conventional diesel engine oil enriched with hBN/Al2O3 nanoparticles. In this study, an optimal composition (0.5 vol.%) of hBN and Al2O3 nanoparticles separately dispersed in SAE 15W40 diesel engine oil by sonication technique. The oil properties were studied by measuring the Viscosity Index (VI), Total Acid Number (TAN), Total Base Number (TBN) and flash point temperature. The results reveal that the nano-oil with hBN nanoparticles could improves or at least maintain the key lubrication properties, though the TAN value is slightly increased. The results presented here may facilitate improvements in the conventional diesel engine oil performance.

Statistical models for predicting wear and friction coefficient of palm kernel activated carbon-epoxy composite using the ANOVA

Purpose The purpose of this study was to propose statistical models for predicting wear and friction coefficient of the palm kernel activated carbon-epoxy composite using the analysis of variance (ANOVA). Design/methodology/approach All the specimens were formed into 10-mm diameter pins of 30-mm length each. The tribological test was conducted using a pin-on-disc tribometer. The results of the coefficient of friction (COF) and the wear rate were then analysed using the ANOVA. Regression analysis was used to derive the predictive equations for both friction coefficient and wear rate. Findings It was found that the most significant parameter that affects the COF is the weight composition, while for the wear rate, it is the operating temperature. The proposed statistical models have 90-94 per cent reliability. Research limitations/implications The equation models are only limited within the tested parameters and ranges in the plastic deformation region. Originality/value These models can be very useful for material design engineers in avoiding the component failures occurring prematurely.

Tribological effects of nano-based engine oil diluted with biodiesel fuel

The aim of this study was to investigate the tribological effects of nano-based engine oil diluted with biodiesel fuel. The nano-oil was prepared by disperse an optimal composition 0.5 vol.% of 70 nm hexagonal boron nitride (hBN) nanoparticles in diesel engine oil using sonication technique. Sample was diluted by difference percentages of B100 biodiesel fuel in range of 5-20 vol.%. The tribological test was performed using a four-ball tribometer. It was found that the addition of biodiesel fuel increases the coefficient of friction (COF) and seizure wears as compared with nano-oil. However, there is no significant effect on the extreme pressure (EP) properties, where the seizure for all tested samples starts to occur at 981 N.