...@whpu.edu.cn Email: wu88888li@163.com Contributed by the Tribology Division of ASME for publication in the J ournal of T ribology . 22 11 2021 28 04 2022 29 04 2022 18 08 2022 lubricant additives quantitative structure tribo-ability relationship antiwear performance...

... study, the quantitative structure tribo-ability relationships (QSTR) between 20 triazine derivatives and their respective extreme-pressure properties as lubricant additives were analyzed by the back propagation neural network (BPNN) method. The BPNN-QSTR model had satisfactory stability and predictive...

.... 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...

... or in the branched chain was exchanged with oxygen, CH 2 , or an NH group. Similarly, the template's benzimidazole ring was replaced with a quinazolinone group. Quantitative structure tribo-ability relationship (QSTR) models by back propagation neural network (BPNN) method were used to study correlations between...

... esters and their wear data were included in the back-propagation neural network (BPNN)-quantitative structure tribo-ability relationship (QSTR) model with two-dimensional (2D) and three-dimensional (3D) QSTR descriptors. The predictive performance of the BPNN-QSTR model is acceptable. The findings...