MWCNT and graphene nanoparticles additives for energy efficiency in engine oil with regression modeling

Quality of engine oil plays vital role in reducing frictional energy loss and enhancing durability. Recently, concept of nano lubricants, which is the suspension of nanoparticles in base lubricants, widely attempted. In the present study, experimental and regression approach has been used to evaluate the rheological properties of graphene/engine oil and MWCNT graphene/ engine oil nanolubricants. Power law index and consistency index values reveal non -Newtonian and shear thinning behavior of the samples. Result shows that dispersion of 1.8% particle volume fraction makes 155.06% and 62.85% increment in viscosity for MWCNT graphene/engine oil and graphene/engine oil nanolubricant, respectively. A novel regression model for the dynamic viscosity of nanolubricant is proposed with temperature, nanoparticle volume fraction and shear rate as parameters. The proposed regression model provides viscosity prediction with deviation within 2.57% (R2, 0.99887). MWCNT graphene/engine oil nanolubricants and regression model provide a cost-effective and eco-friendly approach for enhancement in the properties of lubricant.

Automated summary

The rheological properties of graphene and MWCNT graphene nanolubricants in engine oil were evaluated using experimental and regression methods. The results showed that the nanolubricants significantly increased viscosity. A new regression model was also proposed to predict the viscosity of nanolubricants.