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Synergistic effect of binary systems of nanostructured <scp>MoS<sub>2</sub></scp>/<scp>SiO<sub>2</sub></scp> and <scp>GO</scp>/<scp>SiO<sub>2</sub></scp> as additives to coconut <scp>oil‐derived</scp> grease: Enhancement of physicochemical and lubrication properties

Sooraj Singh Rawat, A. P. Harsha, Om P. Khatri

2021Lubrication Science24 citationsDOI

Abstract

Abstract The present work addresses the use of synergistic blends of two different types of nanomaterials (spherical particles and lamellar sheets) as additives for coconut oil‐based grease formulation to provide the energy‐efficient and sustainable alternative to conventional grease. The spherical SiO 2 nanoparticles are separately blended with 2D lamellar sheets of MoS 2 and graphene oxide (GO) in variable ratio and probed their synergistic effects for enhancement of physicochemical and lubrication properties. The SiO 2 nanoparticles, MoS 2 , and GO nanosheets are prepared by modified sol–gel, hydrothermal reduction, and Hummer's methods, respectively. The 0.05 wt% nanomaterials blends of MoS 2 /SiO 2 (30:70) and GO/SiO 2 (50:50) as optimised doses furnished the maximum reduction in the friction and wear. The combination of rolling friction and low shear properties using the synergistic blend of the spherical nanoparticles (SiO 2 ) and nanosheets (MoS 2 and GO) showed significant improvement in tribological properties. The optimised blends of nanoadditives, that is, MoS 2 /SiO 2 and GO/SiO 2 conserved the energy by 20% and 19%, respectively. These findings suggest that the use of synergistic blends of variable nanomaterials to vegetable oil‐based lubricants can pave a direction for new generation lubricant formulation, where environmental sustainability and energy conservation are on prime importance.

Topics & Concepts

Materials scienceNanomaterialsNanoparticleLubricantLamellar structureChemical engineeringTribologyLubricationNanocompositeNanotechnologyComposite materialEngineeringLubricants and Their AdditivesTribology and Wear AnalysisGear and Bearing Dynamics Analysis