Calculation of polyamides melting point by quantum-chemical method and BP artificial neural networks

Quantitative structure-property relationships (QSPR) for the melting point of the polyamides have been determined. All descriptors were calculated from molecular structures at the B3LYP/6-31G(d) level and a QSPR model was generated by multiple linear regression (MLR). The important molecular descriptors for polyamide melting-point temperatures (T-m) are the number of benzene rings in the backbone chain, the proportion of methylene and acylamino in the backbone chain, the total molecular energy and the atomic charge for the oxygen atom in the acylamino group. The MLR determination coefficient (r(2)) and the standard error of estimation for the model are 0.865 and 21.34 K, respectively. In addition to the nonlinear regression technique, error back-propagation artificial neural networks (BPANN) was used to study the relationships between molecular structures and melting-point temperatures. It is concluded that melting-point temperatures for polyamides can be described by molecular chain rigidity and interchain attractive interactions. The more accurate predicted results were obtained from BPANN.