Tribological and rheological properties of novel MoO3-GO-MWCNTs/5W30 ternary hybrid nanolubricant: Experimental measurement, development of practical correlation, and artificial intelligence modeling

In the present paper, the rheological and tribological measurements of the SAE 5W30 multi-grade engine oil as a base lubricant and a novel ternary combination of molybdenum trioxide (MoO3), graphene oxide (GO), and multi-walled carbon nanotubes (MWCNTs) as nanopowders were conducted in a wide range of solid volume fractions (VF = 0-1.5%), shear rates (SR = 665-12,635 s- 1), and temperatures (T = 5-65 degrees C). As part of a two- step procedure for nanolubricant preparation, a magnetic stirrer and ultrasonic device were utilized for proper dispersion of MWCNT/GO/MoO3 in SAE 5W30. Furthermore, the nanopowders were subjected to X-ray diffraction-based structural analysis. According to diagrams of the shear stress, dynamic viscosity, and power-law index, the analyzed hybrid nanolubricant behaves as a non-Newtonian (pseudoplastic) fluid in all samples. The experimental results revealed that as the temperature drops from 65 degrees C to 5 degrees C, the viscosity of hybrid nano -lubricant increases by a maximum of 92.23% and a minimum of 83.55%. In addition, the highest increase in dynamic viscosity due to the dispersion of nanopowders was 68.54%, which was reported at 65 degrees C and an SR of 2660 s-1. Tribological experiments demonstrated that the dispersion of nanomaterials up to a VF of 0.6% reduces the wear rate and average friction coefficient. Reducing these two parameters improves engine performance, decreases fuel consumption, and reduces engine pollutants. A three-variable correlation was presented to predict dynamic viscosity, which provided reasonable accuracy (R2 = 0.9931). Moreover, an algorithm was developed to optimize the GP-based ANFIS structure, resulting in an extremely accurate model (R2 = 0.999709) for estimating the viscosity of the hybrid nanolubricants.