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• W3009008904 abstract "Abstract In this work, a novel QSPR model for the prediction of hydrocarbon mixtures' superheat limit temperatures (SLTs) was developed solely based on chemical structures and mole fractions of pure compounds. Experimental SLTs of 274 blended fuels were collected from existing references and molecular descriptors for the 25 pure materials were obtained by Gaussian 09 software package. Then the integral additive method was employed for the calculation of mixtures' descriptors and support vector machine (SVM) analysis was carried out to establish the nonlinear QSPR model. The most rigorous way of external validation, “compounds out”, was applied to test the true external predictive capabilities of the model and compared with the latest existing model of Lulu Zhou et al. this model performs better in both internal and external validations. The applicability domains (ADs) of this model were discussed and almost all the points are within the AD area. The use of this model only requires the knowledge of chemical structures and the SLTs of the individuals needn't to be known. The accuracy of the proposed model coupled with the ease of its implementation would definitely ensure quick estimation of SLTs of mixtures." @default.
• W3009008904 created "2020-03-06" @default.
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• W3009008904 date "2020-03-01" @default.
• W3009008904 modified "2023-10-16" @default.
• W3009008904 title "Prediction of superheat limit temperatures for fuel mixtures using quantitative structure-property relationship model" @default.
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• W3009008904 doi "https://doi.org/10.1016/j.jlp.2020.104087" @default.
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