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Evaluation of Antioxidant Properties and Molecular Design of Lubricant Antioxidants Based on QSPR Model
Summary
Not relevant to microplastics — this study uses computational modeling (QSPR) to predict and design better antioxidant additives for lubricating oils, a materials chemistry application unrelated to microplastic pollution.
Two quantitative structure–property relationship (QSPR) models of hindered phenolic antioxidants in lubricating oils were established to help guide the molecular structure design of antioxidants. Firstly, stepwise regression (SWR) was used to filter out essential molecular descriptors without autocorrelation, including electronic, topological, spatial, and structural descriptors, and multiple linear regression (MLR) was used to construct QSPR models based on the screened variables. The two models are statistically sound, with R2 values of 0.942 and 0.941, respectively. The models’ reliability was verified by the frontier molecular orbital energy gaps of the antioxidants. A hindered phenolic additive was designed based on the models. Its antioxidant property is calculated to be 20.9% and 11.0% higher than that of typical commercial antioxidants methyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl) propionate and 2,2′-methylenebis(6-tert-butyl-4-methylphenol), respectively. The structure–property relationship of hindered phenolic antioxidants in lubricating oil obtained by computer-assisted analysis can not only predict the antioxidant properties of existing hindered phenolic additives but also provide theoretical basis and data support for the design or modification of lubricating oil additives with higher antioxidant properties.
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