QSPR Studies on the Prediction of Physicochemical Properties of High Energetic Materials

초록

Numerous effects have been made to derive novel explosive molecules, which are more powerful, yet less insensitive, than those used in current military applications. In deriving promising candidates of explosive molecules, the explosive performance must be accurately estimated. It has generally been accepted in the research on high energetic molecules that explosive performance can be predicted, if accurate estimates of density and heat of formation are provided. The densities of high energetic molecules in the solid states were calculated[1] with a simplified scheme based on molecular surface electrostatic potentials (MSEP).[2] The MSEP scheme for density estimation, originally developed by Politzer et al.,[3] was further modified to calculate electrostatic potential on a simpler van der Waals surface. Forty-one energetic molecules containing at least one nitro group were selected from among a variety of molecular types and density values, and were used to test the suitability of the MSEP scheme for predicting the densities of solid energetic molecules. The absolute average error in densities from our MSEP scheme was 0.039 g/cc (see Fig. 1). Most high energetic molecules exist in the solid state and therefore solid state heats of formation are required to predict explosive performance accurately. Sublimation enthalpies are required to convert the gas phase enthalpies obtained from the quantum chemical calculations to the solid state heats of formation. Fifty-eight energetic molecules containing at least one nitro group and candidates for energetic molecules were selected for this study. Three QSPR eqs developed by using organic molecular sets were examined and applied to our date set. Since the results were not satisfactory, we developed two new QSPR eqs from the molecular descriptors spanning from 0 D to 3 D. The five parameter eqs gave satisfactory correlations (see Fig. 2). We also found that the descriptors developed in this work can applied to predict heats