Computational Analysis of C-H Hydroxylation in Bio-Inspired Monometallic Catalysts

With sustainable energy innovations on the rise but logistical and technological barriers preventing their widespread implementation, it is of paramount importance to increase the sustainability of conventional energy generation for the remainder of its lifecycle. Natural gas, despite being the most environmentally benign of the fossil fuels, is underutilized due to difficulties in storage and transportation. Catalytic conversion of methane to methanol promises to enhance liquefied natural gas usage, but the step of C-H activation is energetically prohibitive. In nature, enzymes including β-Dopamine hydroxylases and lytic polysaccharide monooxygenases (LMPOs) have demonstrated the ability to catalyze this C-H hydroxylation step. Both enzymes exhibit monocopper oxo active sites, but their precise structure and mechanism are unclear. The goals of this research project are as follows:

1. To determine the reaction mechanisms employed by bio-inspired monocopper oxo catalysts
2. To determine the effect of catalyst structure (number of oxygens, number of nitrogenous ligands) on activity
3. To determine which catalysts are sensitive to tuning by adjusting electrophilic and steric parameters

Computational methods are applied to bio-inspired catalytic systems, utilizing quantum mechanical algorithms to optimize molecular geometries, determine transition state structures, and perform energetic analyses. The aim of this work is to provide a comprehensive comparison of different copper oxo catalyst structures, determining which structures give the most favorable catalyst activity and which exhibit the most sensitivity to tuning, potentially enabling more effective catalyst design. Results are subsequently compared to literature data.