Nitrogenase is an enzyme that reduces nitrogen to ammonia, a reaction fundamental to all life on earth. The active site of nitrogenase is an iron-sulfur cluster unique due to an interstitial carbide. However, modeling this carbide moiety to understand its chemical role in dinitrogen reduction has proven synthetically challenging. For example, strongly sigma donating carbonyls and reduced iron in the classical iron carbide carbonyl clusters constrain multiple thiolate and sulfide insertions, limiting their biological relevance. We have turned to develop new FeMoco models by oxidizing in situ the synthetically accessible anionic carbide cluster [NEt4]2[Fe6(µ6-C)(CO)16] and adding our target ligands (thiolate or phosphines) to substitute CO ligands directly. By understanding these ligand substitutions, we hope to design new paths towards modeling the carbide in FeMoco. Our finding was that the carbide from the in situ oxidized cluster ‘Fe6(µ6-C)(CO)16’ was chemically reactive, whereas the carbide in both the stable neutral cluster Fe5C(CO)15 and the starting anionic cluster [NEt4]2[Fe6(µ6-C)(CO)16] are unreactive. We want to understand why the hexa-iron, in situ oxidized cluster ‘Fe6(µ6-C)(CO)16’ is prone to ligand substitution and carbide reactivity, rather than just ligand substitution. The cluster’s instability limited experimental evaluation and structural characterization via single-crystal X-ray diffraction, constraining our understanding of the cluster geometry and its potential role in its reactive carbide center. This drove us to use computational methods, primarily density functional theory (DFT). DFT is a computationally expensive modeling technique compared to Bayesian modeling or principal component analysis. However, we leveraged high-performance compute (HPC) systems to generate significant amounts of high-quality data. We screened functionals and restricted basis sets to calculate overall geometry. We created and validated an appropriate penta-iron cluster model based on its measured infrared results before modeling the hexa-iron cluster Fe6(µ6-C)(CO)16 to assess its geometry.

Modeling neutral, electron-deficient iron carbonyl carbide clusters through density functional theory

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