Non-physical Species in Chemical Kinetic Models: A Case Study of Diazenyl Hydroxy and Diazenyl Peroxide.

Abstract

Predictive chemical kinetic models often consider hundreds to thousands of intermediate species. An even greater number of species are required to generate pressure-dependent reaction networks for gas-phase systems. As this immense chemical search space is being explored using automated 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 non-physical species might obey chemical intuition as well as requirements coded in the software, e. g., obeying element electron valence constraints, and may consequently remain unnoticed. Non-physical species become an acute problem when their presence affects a model observable. Correcting a pressure-dependent network containing a non-physical species may significantly affect the computed rate coefficient. The present work discusses and analyzes two specific cases of such species, diazenyl hydroxy (⋅N=NOH) and diazenyl peroxide (⋅N=NOOH), both previously suggested as intermediates in nitrogen combustion systems. A comprehensive conformational search did not identify any non-fragmented energy well, and energy scans performed for diazenyl peroxide (⋅N=NOOH), at DFT and CCSD(T) show that it barrierlessly decomposes. 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.