Evaluation of Anti-wear Properties of Different Vegetable Oils Based on QSPR Model

Liu, Jianfang; Zhang, Rongrong; Yang, Sicheng; Liu, Ting; Yi, Chenglingzi; Zhang, Yaoyun; Jia, Dechang

doi:10.1007/s11249-023-01704-9

Cited by 6 publications

(3 citation statements)

References 39 publications

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“…If the scatter points in the P-P diagram are closer to a diagonal linear distribution, it indicates that the data is more satisfied with the normal distribution [25]. The points in the P-P plots (Figure 2) of models 1 and 2 are approximately distributed in a diagonal straight line, and the dispersion of both models is diagonally distributed, which proves that the two models are reliable.…”

Section: Reliability Of Modelmentioning

confidence: 84%

“…The adjusted coefficient of determination (R 2 ), the existence of multicollinearity, the root mean square error (RMSE), and the value of Durbin-Watson (DW) were used as evaluation criteria for selecting the best prediction model [25]. It is generally considered that R 2 > 0.6 indicates that the model is acceptable and R 2 > 0.8 indicates that the model has a high degree of fit.…”

Section: Construction Of Qspr Modelmentioning

confidence: 99%

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Evaluation of Antioxidant Properties and Molecular Design of Lubricant Antioxidants Based on QSPR Model

Liu,

Zhang,

et al. 2023

Lubricants

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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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Section: Reliability Of Modelmentioning

confidence: 84%

Section: Construction Of Qspr Modelmentioning

confidence: 99%

Evaluation of Antioxidant Properties and Molecular Design of Lubricant Antioxidants Based on QSPR Model

Liu,

Zhang,

et al. 2023

Lubricants

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“…Real images of the sample room temperature are depicted in Figure 1, while the melting points of fatty acids a pour points of vegetable oils are presented in Table 1. The molecular structures of th fatty acids has been previously reported and are not reiterated here [22].…”

Section: Raw Materialsmentioning

confidence: 96%

Prediction of Lubrication Performances of Vegetable Oils by Genetic Functional Approximation Algorithm

Liu,

Zhang,

Yang

et al. 2024

Lubricants

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Vegetable oils, which are considered potential lubricants, are composed of different types and proportions of fatty acids. Because of their diverse types and varying compositions, they exhibit different lubrication performances. The genetic function approximation algorithm was used to model the quantitative structure–property relationship between fatty acid structure and the wear scar diameter and friction coefficients measured by four-ball friction and wear tests. Based on the models with adjusted R2 greater than 0.9 and fatty acid compositions of vegetable oils, the wear scar diameter and friction coefficients of Xanthoceras sorbifolia bunge oil and Soybean oil as validation oil samples were predicted. The difference between the predicted and experimental values was small, indicating that the models could accurately predict the lubrication performances of vegetable oils. The lubrication performances of 14 kinds of vegetable oils were predicted by GFA-QSPR models, and the primary factors influencing their lubrication properties were studied by cluster analysis. The results show that the content of C18:1 has a positive effect on the lubrication performances of vegetable oils, while the content of C18:3 has a negative effect, and the length of the carbon chain of fatty acids significantly affects their lubrication properties.

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Comprehensive quality evaluation of anti-wear properties and oxidation stability of different vegetable oils based on QSPR-factor analysis

Zhang,

Yang,

Liu

et al. 2024

Fuel

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Evaluation of Anti-wear Properties of Different Vegetable Oils Based on QSPR Model

Cited by 6 publications

References 39 publications

Evaluation of Antioxidant Properties and Molecular Design of Lubricant Antioxidants Based on QSPR Model

Evaluation of Antioxidant Properties and Molecular Design of Lubricant Antioxidants Based on QSPR Model

Prediction of Lubrication Performances of Vegetable Oils by Genetic Functional Approximation Algorithm

Comprehensive quality evaluation of anti-wear properties and oxidation stability of different vegetable oils based on QSPR-factor analysis

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