Prediction of Glass Transition Temperatures for some Polyimides using QSPR analysis

Quantitative structure-properties relationship (QSPR) has been applied to modeling and predicting the glass transition temperature (Tg) of forty aromatic heterocyclic polyimides. Structures of these compounds were optimized geometrically by Hyperchem7.0 and molecular descriptors were obtained by Dragon5.5 software. Multiple linear regression (MLR) based on stepwise variable selection was employed to find the most convenient quantitative models. Two models were suggested, one model having seven descriptors (R = 0.966, Q2cv = 0.945, F = 65.4, Std. Error of the Estimate =10.26) and other model involving three descriptors (R=0.867, F= 36.3, Std. Error of the Estimate =18.87). Cross validation to evaluate the reliability of first model was performed by MATLAB software. The effect of number of descriptors on the correlation coefficient (R) and F-ratio were considered. It was observed that R and F are increased due to increasing the number of descriptors. The best model is that has higher R, F and smaller number of descriptors

کلیدواژه ها:

Molecular modeling ، Quantitative Structure-Property Relationship (QSPR) ، Multiple linear regression ، Glass transition temperature ، polyimide ، processability