Non-physical species in chemical kinetic models: A case study of diazenyl hydroxy and diazenyl peroxide

Predictive chemical kinetic models often consider hundreds to thousands of intermediate chemical species. An even greater number of species, that might not participate in the model directly, are required to generate pressure-dependent reaction networks for gas-phase systems. As this immense chemical search space is being explored using automated software tools by applying reaction templates, it is probable that non-physical species will infiltrate the model without being recognized by the compute or a human as such. These nonphysical species might obey chemical intuition as well as requirements coded in the software, e.g., obeying electron valence constraints of chemical elements, and may consequently remain unnoticed. Nonphysical species become an acute problem when their presence affects the model observables. The present work discusses and analyzes two specific cases of such species, diazenyl hydroxy (·NNOH) and diazenyl peroxide (·NNOOH), both previously suggested as intermediates in nitrogen combustion systems. A comprehensive conformational search did not identify any non-fragmented energy well for either of the two species, and energy scans performed for diazenyl peroxide (·NNOOH), both at DFT and CCSD(T), show that they barrierlessly decompose. This work highlights a broad implication for future automated chemical kinetic model generation, and provides a significant motivation to standardize non-physical species identification in chemical kinetic models.