Research Progress on Flash Point Prediction

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• 作者：Xinshuai Liu ; Zhenyi Liu
• 刊名：Journal of Chemical & Engineering Data
• 出版年：2010
• 出版时间：September 9, 2010
• 年：2010
• 卷：55
• 期：9
• 页码：2943-2950
• 全文大小：125K
• 年卷期：v.55,no.9(September 9, 2010)
• ISSN：1520-5134

文摘

Flash point is one of the major physical and chemical properties used to determine the fire and explosion hazards of liquids; therefore, the prediction of flash points is an important safety consideration. In this paper, flash point prediction methods based on vapor pressure, molecular structure, composition range, and boiling point of flammable liquids are reviewed, respectively. Le Chatelier’s rule and Antoine equations are used in the correlation between vapor pressure and flash point. Research on the correlations between flash point and composition range of the mixture has focused on flash point predictions for binary and ternary solutions, and further investigation for multicomponent solutions is required in the future. With regard to the correlation between molecular structure and flash point, some key breakthroughs have been made through quantitative structure−property relationship (QSPR) analysis. In particular, the artificial neural network (ANN) in QSPR is one possible correlation technique because of its nonlinear property and high accuracy and has the potential for wide application.