Systematic performance evaluation of gasoline molecules based on quantitative structure-property relationship models. (16th January 2021)

• Record Type: Journal Article
• Authors: Cai, Guangqing; Liu, Zhefu; Zhang, Linzhou; Shi, Quan; Zhao, Suoqi; Xu, Chunming
• Is Part Of: Chemical engineering science. Volume 229(2021)
• Publication Date: 2021-01-16
• Subjects: Gasoline -- QSPR -- Molecular structure -- Molecular management; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2020.116077
• Languages: English
• ISSNs: 0009-2509

Abstract

Highlights: A systematic gasoline molecular performance evaluation model was established. The optimal gasoline molecules using advanced property prediction model was screened. The molecular performance distribution characteristics of blending stocks were compared. The effect of conversion pathway on the molecular performance was investigated. Abstract: The future production of clean gasoline requires the evaluation of molecular performance. In this paper, we established a systematic performance evaluation model for molecules in the gasoline range. Antiknock, cleanliness, power, stability, and evaporation performance were investigated and are related to the production of high-quality and clean gasoline. Corresponding quantitative structure–property relationship (QSPR) models were developed to predict the octane number, yield sooting index (YSI), combustion heat, unsaturated bond content, and Reid vapor pressure. The obtained models precisely predict these key properties using only the molecular structure as the input. Several applications were made to show the benefit of the molecular performance evaluation model, including the screening of optimal gasoline molecules, the molecular performance distribution of gasoline mixtures, and the effect of the gasoline molecular conversion pathway. The developed model is potentially a useful tool for the identification of optimal gasoline molecules and related process design.