A Three-Dimensional Quantitative Structure Tribo-Ability Relationship Model
Xinlei Gao, Zhan Wang, Hong Zhang, Kang Dai · Journal of Tribology · 2014
The prediction of lubrication characteristics for compounds through tribological models would aid in the discovery of new lubricant additives and improved lubricant design. But until recently, the field of tribological prediction has been sparse and not systematic. Tribological processes are complex and involve molecular energy exchange as well as conformation transitions. We have developed a platform of a “quantitative structure tribo-ability relationship (QSTR),” which enables us to introduce well-developed quantitative structure–activity relationships (QSAR) methods into tribology systematically. The present study applies “evaluation of infrared vibration-based” (EVA) descriptors, which are three-dimensional (3D) QSAR descriptors to simulate infrared (IR) vibration properties of molecules, in order to establish the QSTR prediction model. As structural changes take place under friction loads, the EVA descriptors characterize both molecular energy and conformations. The results show a strong correlation and robust predictability of the EVA model to tribological parameters. The approach paves a way to a systematic QSTR.