Systematic performance evaluation of gasoline molecules based on quantitative structure-property relationship models

被引：19

作者：

Cai, Guangqing ^{[1
,2
]}

Liu, Zhefu ^{[3
]}

Zhang, Linzhou ^{[1
,2
]}

Shi, Quan ^{[1
,2
]}

Zhao, Suoqi ^{[1
,2
]}

Xu, Chunming ^{[1
,2
]}

机构：

[1] China Univ Petr, State Key Lab Heavy Oil Proc, Beijing 102249, Peoples R China

[2] China Univ Petr, Petr Mol Engn Ctr PMEC, Beijing 102249, Peoples R China

[3] Chinese Acad Sci, Computat Intelligence & Ind Big Data Grp, Quanzhou Inst Equipment Mfg, Luoshan St 166, Jinjiang City 362216, Fujian, Peoples R China

来源：

CHEMICAL ENGINEERING SCIENCE | 2021年 / 229卷

基金：

国家重点研发计划; 中国国家自然科学基金;

关键词：

Gasoline; QSPR; Molecular structure; Molecular management; AUTO-IGNITION TEMPERATURES; ORGANIC-COMPOUNDS; FLASH POINTS; LIQUID VISCOSITY; OCTANE NUMBER; PREDICTION; HYDROCARBONS; REPRESENTATION; DENSITY; OIL;

D O I：

10.1016/j.ces.2020.116077

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

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 rela-tionship (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. (c) 2020 Elsevier Ltd. All rights reserved.

引用

页数：11

共 60 条

[1] Structural group contribution method for predicting the octane number of pure hydrocarbon liquids [J].