Boundary Lubricity of Vegetable-Oil-Derived Trimethylolpropane (TMP) Ester

Abstract

Vegetable-oil-based biolubricants are an excellent alternative to conventional lubricants. Instead of focusing on novel feedstocks, these biolubricants should be further elucidated based on their fatty acid composition, which influences their tribological properties. Therefore, the study utilises gene expression programming (GEP) to derive a boundary lubricity model for vegetable-oil-derived trimethylolpropane (TMP) esters, considering the fatty acid composition (saturation and monounsaturation levels), load and speed. Neat vegetable oil and blends from seven feedstocks are selected following a wide range of fatty acid profiles to synthesise TMP esters using a two-stage transesterification process. The TMP esters are spin-coated on wear discs that are subsequently rotated against a ball using a purpose-built tribometer. The frictional performance of the TMP esters with balanced saturation and monounsaturation levels of fatty acid are measured to improve it at higher speeds. The GEP model is statistically evaluated by adopting the friction data, a showing good generalisation and predictability capability. The model demonstrates that friction decreases with increasing saturation levels of the TMP ester. The GEP model for vegetable oil TMP esters allows for the tribological performance prediction of TMP esters following the fatty acid profile, providing a platform to optimise such biolubricant for desired applications.

Keywords

• fatty acid composition
• tribometer
• spin coating
• thin film
• physicochemical
• gene expression programming