Abstract
Contributions to the growing environmental concerns by internal combustion engines (ICEs) is the impetus of this research.
Therefore, the tribological behavior of lubricants formulated with nano/mineral, nano/bio, and bio/mineral combinations were investigated for the improvements to ICE performance by reducing friction, wear, fuel consumption and exhaust emissions. Mineral-based multigrade engine oil (15W40) was chosen as the reference oil to govern the research. Coconut oil (CCO) was chosen with 15W40 as bio and mineral-base stocks respectively for sample formulations. Graphene (G), Al2O3, TiO2, Al2O3/G, TiO2/G and TiO2/reduced graphene oxide (r-GO) were utilized as nano-additives to blend with both mineral and bio-based formulations. Identity of the selected nanomaterials were confirmed using X-ray powder diffraction (XRD), transmission electron microscopy(TEM), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared (FT-IR) and Raman analyses. Identified substandard of CCO were improved and characterized using differential scanning calorimetry (DSC), pour point, titration, viscometry, simultaneous thermal analysis (STA), rheometric and FT-IR analyses. Factors influencing the dispersion stability of nano/mineral and nano/bio formulations were investigated, and optical absorbance and stability observation tests were used to optimize the performance, with the results presented and discussed.
Friction tests were performed using a linear reciprocating tribometer in 3 Phases to analyze the effect of formulated lubricants at elevated temperatures using piston ring and cylinder liner segments of an ICE as test specimens. Wear scars of test specimens were analyzed using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and 3D non-contact optical profilometry to investigate morphologies, elemental deposition, and surface texture of wear surfaces respectively. Specific fuel consumption andexhaust emissions were tested using a dynamometer test-rig and an exhaust analyzer. Industrial generator was utilized for used engine oil sample analysis.
Therefore, the tribological behavior of lubricants formulated with nano/mineral, nano/bio, and bio/mineral combinations were investigated for the improvements to ICE performance by reducing friction, wear, fuel consumption and exhaust emissions. Mineral-based multigrade engine oil (15W40) was chosen as the reference oil to govern the research. Coconut oil (CCO) was chosen with 15W40 as bio and mineral-base stocks respectively for sample formulations. Graphene (G), Al2O3, TiO2, Al2O3/G, TiO2/G and TiO2/reduced graphene oxide (r-GO) were utilized as nano-additives to blend with both mineral and bio-based formulations. Identity of the selected nanomaterials were confirmed using X-ray powder diffraction (XRD), transmission electron microscopy(TEM), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared (FT-IR) and Raman analyses. Identified substandard of CCO were improved and characterized using differential scanning calorimetry (DSC), pour point, titration, viscometry, simultaneous thermal analysis (STA), rheometric and FT-IR analyses. Factors influencing the dispersion stability of nano/mineral and nano/bio formulations were investigated, and optical absorbance and stability observation tests were used to optimize the performance, with the results presented and discussed.
Friction tests were performed using a linear reciprocating tribometer in 3 Phases to analyze the effect of formulated lubricants at elevated temperatures using piston ring and cylinder liner segments of an ICE as test specimens. Wear scars of test specimens were analyzed using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and 3D non-contact optical profilometry to investigate morphologies, elemental deposition, and surface texture of wear surfaces respectively. Specific fuel consumption andexhaust emissions were tested using a dynamometer test-rig and an exhaust analyzer. Industrial generator was utilized for used engine oil sample analysis.
| Original language | English |
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| Publication status | Published - 3 Oct 2022 |