Estimating antiwear properties of esters as potential lubricant-based oils using QSTR models with CoMFA and CoMSIA
Zhan Wang, Tingting Wang, Guoyan Yang, Xinlei Gao, Kang Dai · Friction · 2017
Abstract Comparative molecular field analysis and comparative molecular similarity indices analysis were employed to analyze the antiwear properties of a series of 57 esters as potential lubricant-based oils. Predictive 3D-quantitative structure tribo-ability relationship models were established using the SYBYL multifit molecular alignment rule with a training set and a test set. The optimum models were all shown to be statistically significant with cross-validated coefficients q 2 > 0.5 and conventional coefficients r 2 > 0.9, indicating that the models are sufficiently reliable for activity prediction, and may be useful in the design of novel ester-based oils.