Optimization Strategies for the Selection and Prediction of Superlubricity Isotropic Compounds: Integrating Screening Factors with Qstr Analysis

Abstract

In the face of increasing global energy consumption, green chemistry has attracted much attention. Liquid crystal lubricants are difficult to promote due to conditions. Therefore, in this study, 40 isotropic organic small molecule compounds with liquid crystal-like properties were explored as alternatives to liquid crystal lubricants. The(Quantitative structure tribo-ability relationship)QSTR method was used to predict the tribological properties of the compounds based on their structures, and an innovative screening factor G was proposed, which can effectively identify compounds with excellent friction-reducing properties through screening and modeling analysis, thus greatly improving the screening efficiency. This provides new avenues for tribological lubricant screening, which is significant for exploiting potential tribological properties.

Keywords: Quantitative structure tribo-ability relationship model, CoMSIA-both, polyimide, superlubricity.