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Prediction the Normal Boiling Points of Primary, Secondary and Tertiary Liquid Amines from their Molecular Structure Descriptors

Saaidpour S., Bahmani A., Rostami A.

Computational Methods in Science and Technology

2015

Vol. 21, No. 4

201--210

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 semi-empirical 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).

Fragment-topological Descriptors for QSPR Estimation of the Normal Boiling Point Temperature of Normal and Branched Hydrocarbons

Kozioł J.

Polish Journal of Chemistry

2009

Vol. 83, nr 12

2173-2187

The new QSPR correlation equation was developed for the estimation of the boiling points of special families of alkanes. This equation includes contributions depending on the total number of carbon atoms forming a mol ecule and the fragment term represented as an explicit function of some basic topological characteristics of the molecular structure. The original mathematical form for description of non-linear contribution is suggested. A five-parameter correlation with the squared correlation coefficient R2 = 0.9993 gives excellent predictions for 168 saturated hydrocarbons, with standard deviation SD = 2 K and mean error of plus or minus 1.43 K. All the parameters in volved in these equations can be derived solely from the chemical structure.