A systematic approach for thermal stability predictions of chemicals and their risk assessment: Pattern recognition and compounds classification based on thermal decomposition curves

Firstly, DSC thermograms (or curves) are analyzed to identify similar decomposition patterns in order to develop a clustering based on their overall thermal behavior instead of their structural similarities. Secondly, the repartition of the structural groups in the clusters is evaluated in order to determine the most influential functional groups on the thermal decomposition behavior. From this analysis, a systematic classification is developed to assign molecules of unknown thermal behavior to a particular cluster. Thirdly, predictive models of thermal characteristics are constructed within the different classes allowing predicting the entire DSC curve. The primary classification based on the pattern recognition increases the predictive performance of the regressions models