Estimating antiwear properties of ionic liquids as lubricant additives using a QSTR model

The antiwear properties of ionic liquids (ILs) as lubricant additives were studied with polyethylene glycol (PEG) used as the lubricant base oil. The quantum parameters of the ILs were calculated using a Hartree-Fock ab initio method. Correlation between the scale of the wear scar diameter and quantum parameters of the ILs was studied by multiple linear regression (MLR) analysis. A quantitative structure tribo-ability relationship (QSTR) model was built with a good fitting effect and predictive ability. The results show that the entropy of the ILs is the main descriptor affecting the antiwear performance of the lubricant system. To improve the antiwear performance of the lubricants, the entropy of the system should be decreased, reducing the system randomness and increasing the system regularity. A major influencing factor on the entropy of a system is the intra-and intermolecular hydrogen bonds present. Therefore, enhanced antiwear properties of lubricants could be achieved with a three-dimensional netlike structure of lubricant formed by hydrogen bonding.