Quantitative structure-property relationship of glass transition temperatures for organic compounds

The glass transition temperatures (<i>T</i>_gs) of materials used in the manufacture of organic light-emitting diodes (OLEDs) determine their thermal stability. Three Dragon descriptors, TPC, RBF and TDB04s, were adopted to develop quantitative structure-property relationships (QSPR) for the prediction of the <i>T</i>_gs of 66 compounds (Data Set I) for OLED application, by applying random forest (RF) and support vector machine (SVM). The RF Model A, based on a training set (44 compounds), was validated with a test set (22 compounds). The RF Model A possesses a coefficient of determination <i>R</i>² of 0.942 and a root mean square (rms) error of 10.750 K for the training set and <i>R</i>² of 0.909 and rms error of 11.102 K for the test set, which are more accurate than the results from the SVM model. The RF Model A was further validated with 63 OLED molecules (Data Set II). Moreover, the three Dragon descriptors (TPC, RBF and TDB04s) were used to build another <i>T</i>_g QSPR model (named RF Model B) for a large dataset of 1934 OLED molecules (Data Set III), which achieved rms errors of 16.79 K for Data Set III, 22.89 K for Data Set I and 20.17 K for Data Set II.