| Sumario: | Estimating thermal stability of chemical components using computational methods provides a reliable and useful means to minimize the number of experiments needed and to advance an alternative to performing experiments on nonstable chemicals, hence providing a safer methodology of attaining the needed data. In this work, predictive models using the Quantitative Structure Property Relationship (QSPR) were developed to estimate the chemical reactivity related properties for noncyclic hydrazines. QSPR models can be used to predict calorimetric experimental data, such as onset temperature and heat of decomposition, using entities derived from the molecular structure for a set of 32 reactive noncyclic hydrazines. Molecular descriptors that are strongly dependant on geometry were calculated after molecular geometry optimization, such as eHOMO, eLUMO, dipole moment (DM), total energy and others. These descriptors describe the thermal stability of hydrazines more effectively. Genetic function approximation analysis was used to predict the final model for each property. The reliability of the QSPR model was assessed by statistical parameters, such as R2, R2(CV) and F value, which are 0.895, 0.833 and 29.201 for onset temperature and 0.978, 0.660 and 95.133 for heat of decomposition.
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