Estimating antiwear properties of esters as potential lubricant-based oils using QSTR models with CoMFA and CoMSIA
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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 q2 > 0.5 and conventional coefficients r2 > 0.9, indicating that the models are sufficiently reliable for activity prediction, and may be useful in the design of novel ester-based oils.
Keywordsquantitative structure tribo-ability relationship antiwear properties lubricant-based oils
This work was supported by the National Nature Science Foundation of China (NSFC, No. 51675395).
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