Thermal decomposition of 1,5-dinitrobiuret (DNB): direct dynamics trajectory simulations and statistical modeling

J Phys Chem A. 2011 Jul 21;115(28):8064-72. doi: 10.1021/jp203889v. Epub 2011 Jun 24.

Abstract

A large set of quasi-classical, direct dynamics trajectory simulations were performed for decomposition of 1,5-dinitrobiuret (DNB) over a temperature range from 4000 to 6000 K, aimed at providing insight into DNB decomposition mechanisms. The trajectories revealed various decomposition paths and reproduced the products (including HNCO, N(2)O, NO(2), NO, and water) observed in DNB pyrolysis experiments. Using trajectory results as a guide, structures of intermediate complexes and transition states that might be important for decomposition were determined using density functional theory calculations. Rice-Ramsperger-Kassel-Marcus (RRKM) theory was then utilized to examine behaviors of the energized reactant and intermediates and to determine unimolecular rates for crossing various transition states. According to RRKM predictions, the dominant initial decomposition path of energized DNB corresponds to elimination of HNNO(2)H via a concerted mechanism where the molecular decomposition is accompanied with intramolecular H-atom transfer from the central nitrogen to the terminal nitro oxygen. Other important paths correspond to elimination of NO(2) and H(2)NNO(2). NO(2) elimination is a simple N-N bond scission process. Formation and elimination of nitramide is, however, dynamically complicated, requiring twisting a -NHNO(2) group out of the molecular plane, followed by an intramolecular reaction to form nitramide before its elimination. These two paths become significant at temperatures above 1500 K, accounting for >17% of DNB decomposition at 2000 K. This work demonstrates that quasi-classical trajectory simulations, in conjunction with electronic structure and RRKM calculations, are able to extract mechanisms, kinetics, dynamics and product branching ratios for the decomposition of complex energetic molecules and to predict how they vary with decomposition temperature.