Automatic Creation of Missing Groups through Connectivity Index for Pure-Component Property Prediction

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• 作者：Rafiqul Gani ; Peter M. Harper ; and Martin Hostrup
• 刊名：Industrial & Engineering Chemistry Research
• 出版年：2005
• 出版时间：August 31, 2005
• 年：2005
• 卷：44
• 期：18
• 页码：7262 - 7269
• 全文大小：300K
• 年卷期：v.44,no.18(August 31, 2005)
• ISSN：1520-5045

文摘

A common frustration of using property models in general and group contribution models inparticular is that the selected model may not have all the needed parameters, such as groupsand/or their contributions needed to represent the molecular structure of the compound whoseproperties are to be estimated. Also, even if the groups are available, for some chemicals the setof groups may not be able to provide an acceptable level of prediction accuracy. One way toaddress these limitations with the group contribution approach is to add new groups. Additionof new groups, however, normally requires experimental data so that the new groups can bedefined and their contributions estimated, which requires time and resources and is, therefore,not convenient for the model user. In this paper, a group contribution⁺ approach for pure-component properties, where missing groups are created and their contributions predictedthrough a set of zero-order and first-order connectivity indices, is presented.