期刊名称：Computational Methods in Science and Technology
印刷版ISSN：1505-0602
出版年度：2015
卷号：21
期号：4
页码：201-210
DOI：10.12921/cmst.2015.21.04.004
出版社：Poznan Supercomputing and Networking Center
摘要：In this article, at first, a quantitative structure–property relationship (QSPR) model for estimation of the normal boiling point of liquid amines is developed. QSPR study based multiple linear regression was applied to predict the boiling points of primary, secondary and tertiary amines. The geometry of all amines was optimized by the semiempirical method AM1 and used to calculate different types of molecular descriptors. The molecular descriptors of structures were calculated using Molecular Modeling Pro plus software. Stepwise regression was used for selection of relevance descriptors. The linear models developed with Molegro Data Modeller (MDM) allow accurate estimate of the boiling points of amines using molar mass (MM), Hansen dispersion forces (DF), molar refractivity (MR) and hydrogen bonding (HB) (1◦ and 2◦ amines) descriptors. The information encoded in the descriptors allows an interpretation of the boiling point studied based on the intermolecular interactions. Multiple linear regression (MLR) was used to develop three linear models for 1◦ , 2◦ and 3◦ amines containing four and three variables with a high precision root mean squares error, 15.92 K, 9.89 K and 15.76 K and a good correlation with the squared correlation coefficient 0.96, 0.98 and 0.96, respectively. The predictive power and robustness of the QSPR models were characterized by the statistical validation and applicability domain (AD).
