Computational study of ammonia generation by iron(III) and iron(IV) complexes supported by trigonal bipyramidal iron

High-valent species such as terminal iron nitrides (Fe(sic)N) are carried out for many organic and inorganic transformations. Simultaneously, they provide significant insight into the reactivity of various metalloenzyme as they involved in the reaction of nitrogenase enzyme. Various biomimetic model complexes were reported to understand nitrogenase enzyme's reactivity. In this framework, Peters et al. have published the facile formation of intermediate species [(TPB)Fe-III/IV(sic)N](0/1+) from the complex [(TPB)FeN2] (here, TPB = tris(o-diisopropylphosphinophenyl) borane. However, all species were thoroughly synthesized and characterized. But the mechanism is still elusive in terms of reactivity and the roles of intermediate species. In this work, we have tried to explore the mechanism of ammonia generation from these high-valent [(TPB)Fe-III/IV(sic)N](0/1+) species employing the experimental conditions. Our computed results shows a very small energy barrier of 6.7 kJ/mol for the first transition state of protonation by the [(TPB)Fe-III(sic)N] species (path1) in the N-H bond activation of path1, however comparatively large energy barrier was reported for path2. From this reaction mechanism, it is established that species [(TPB)Fe-III(sic)N] is more reactive than [(TPB)Fe-IV(sic)N](+). The reactivity difference between these two species is mainly due to the nature of Fe(sic)N bond, its basicity and electron delocalization during the -N-H bond activation. Comprehensive electronic structure investigation of the transition state reveals that the substrate will follow the low energy sigma-type pathway and the electron from the N-H bond electron will go in the sigma(2)(z) orbital. However, the high-energy pi-type pathway, where the N-H bond electron will go in the pi*(xz) orbital. The spectroscopic parameters (Absorption, and Mossbauer) computed for some species, are compared to experimental observation to get belief on the computed data.