PREDICTION OF NORMAL BOILING POINTS FOR A DIVERSE SET OF INDUSTRIALLY IMPORTANT ORGANIC-COMPOUNDS FROM MOLECULAR-STRUCTURE

被引：59

作者：

WESSEL, MD ^{[1
]}

JURS, PC ^{[1
]}

机构：

[1] PENN STATE UNIV, DEPT CHEM, UNIVERSITY PK, PA 16802 USA

来源：

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES | 1995年 / 35卷 / 05期

关键词：

D O I：

10.1021/ci00027a008

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Models that accurately predict normal boiling points for organic compounds containing heteroatoms have been developed with regression and computational neural network methods. The structures of the compounds are represented by calculated structural descriptors. Two models are presented-one for a set of 277 compounds containing only O, S, and halogens, and a second for a set of 104 compounds all containing N. Root-mean-square errors of about 9 K result. The accuracy of prediction of these models is compared to a widely used group contribution method for boiling point estimation.

引用

页码：841 / 850

页数：10

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