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.