ArticleScientific reports2023
Laboratory investigation of GO-SA-MWCNTs ternary hybrid nanoparticles efficacy on dynamic viscosity and wear properties of oil (5W30) and modeling based on machine learning.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Thermal Conductivity Enhancement of Cu- and Ag-Decorated MWCNT Hybrid Nanofluids Synthesized via Probe Ultrasonication.ChemistryOpen · 2026Article
- Bayesian-optimized machine learning and experimental study of Al₂O₃-CuO hybrid nanofluid thermal performance in turbulent circular tube flow.Scientific reports · 2025Article
- PTEN as a prognostic factor for radiotherapy plus immunotherapy response in nasopharyngeal carcinoma.Journal of nanobiotechnology · 2025Article
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Abstract
In the present study, the properties of ternary hybrid nanofluid (THNF) of oil (5W30) - Graphene Oxide (GO)-Silica Aerogel (SA)-multi-walled carbon nanotubes (MWCNTs) in volume fractions ([Formula: see text] of 0.3%, 0.6%, 0.9%, 1.2%, and 1.5% and at temperatures 5 to 65 °C has been measured. This THNF is made in a two-step method and a viscometer device made in USA is used for viscosity measurements. The wear test was performed via a pin-on-disk tool according to the ASTM G99 standard. The outcomes show that the viscosity increases with the increase in the [Formula: see text], and the reduction in temperature. By enhancing the temperature by 60 °C, at [Formula: see text] = 1.2% and a shear rate (SR) of 50 rpm, a viscosity reduction of approximately 92% has been observed. Also, the results showed that with the rise in SR, the shear stress increased and the viscosity decreased. The estimated values of THNF viscosity at various SRs and temperatures show that its behavior is non-Newtonian. The efficacy of adding nanopowders (NPs) on the stability of the friction and wear behavior of the base oil has been studied. The findings of the test display that the wear rate and friction coefficient increased about 68% and 4.5% for [Formula: see text] = 1.5% compared to [Formula: see text] = 0. Neural network (NN), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Gaussian process regression (GPR) based on machine learning (ML) have been used to model viscosity. Each model predicted the viscosity of the THNF well, and Rsquare > 0.99.
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