Iron precatalysts of the form ArBIANFeBr2 (Ar = dpp or Mes; dpp = 2,6-diisopropylphenyl, Mes = 2,4,6-trimethylphenyl; BIAN = Bis(imino)acenaphthene) have been shown to have high catalytic activity in hydrosilylation reactions upon in situ reduction. While nearly quantitative hydrosilylation yields can be achieved at low catalyst loading and mild conditions with dpp-subsitution on the BIAN ligand, other precatalyst ligand substituents provide significantly lower yields. A model for the active iron catalyst, dppBIANFeCOD (COD = cylcooctadiene), has been shown to result in a high yield for the hydrosilylation of 1-hexene with phenylsilane, comparable to the yield obtained from its corresponding precatalyst. To determine whether these results are impacted by the structure of the active catalyst, along with the in situ reduction process, the electronic structure of a series of reduced iron catalysts has been investigated computationally. Specifically, a series of model structures for proposed active catalysts of the form ArBIANFe(COD) species with various substitution patterns on the aryl groups of the ligand have been targeted for the computational exploration of electronic structure. Density Functional theory (DFT) calculations have been performed at the B3LYP level of theory on selected compounds within the series of iron-COD catalysts in order to predict properties before they are synthesized. Geometry optimization, Mössbauer parameter calculations, and numerical frequency computations are being investigated, and computed values have been compared to experimental data where possible. Thus far, catalysts are generally predicted to have high spin iron(I) centers antiferromagnetically coupled to a redox-active, monoreduced BIAN ligand as the lowest energy electronic structure outcome. Computed Mössbauer parameters will be used to select experimental catalyst targets in order to identify whether an optimal computed Mössbauer isomer shift range for the model catalyst may be identified to produce higher yields for catalytic hydrosilylation reactions.

Computational analysis of iron cyclooctadiene catalysts supported by bis(imino)acenaphthene ligands

ACS Spring 2022

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