Quantitative Structure-Properties Relationship of Lubricating Oil Additives and Molecular Dynamic Simulations Studies of Diamond-Like-Carbon (DLC)

Quantitative Structure-Properties Relationship (QSPR) and molecular dynamics simulations studies were carried out on the ۵۳ lubricating oil additives and hydrogen-containing DLC (a-C: H). Good QSPR model was developed along with squared correlation coefficient (R۲), adjusted squared correlation coefficient (R۲adj), leave one out cross-validation coefficient (Q۲) and the external validation (R۲ext) of values ۰.۸۰۷۲۰۸, ۰.۷۶۳۶۷۴, ۰.۶۸۸۶۷ and ۰.۶۲۹۷ respectively which shows that model I was reliable and satisfactory. Molecular dynamics simulation binding energy calculations between the lubricant additives and the hydrogen-containing DLC (a-C: H) crystals surface revealed that the best molecular dynamic binding energy was found to be -۲۱۱۲.۰۶ kcal/mol and was found to be better than the one reported by other researchers. Moreover, the lubricant additive with compound number ۵۰** (S-(۲-(benzo[d]thiazol-۲-ylamino)-۲-oxoethyl) O-hexyl carbonodithioate) was found to have the best molecular dynamic binding energy of -۲۱۱۲.۰۶ kcal/mol which conformed with excellent best-normalized onset temperature (Tonset) ۲.۴۶۷K of the same compound. Moreover, Table ۷ revealed that the time(s) used for every simulation varies from ۱۲۶۸۳.۱۳s to ۱۳۸۸۴۱.۰۹s for all the studied additives. This investigation will help in rational additive design and synthesis of new and better lubricant additives with predetermined promising binding energy and onset temperature (Tonset) and will provide valuable information for the understanding of dynamic binding energy between DLC substrate and the new compounds and will give the way toward the discovery of novel lubricating oil additives that can withstand high dynamic working temperature and also resist wearing and frictions.

کلیدواژه ها:

QSPR ، Lubricant additive: Diamond-Like-Carbon (DLC): Hydrogen-containing DLC (a-C: H): Density Functional Theory: Genetic Function Algorithm: Molecular dynamic