Ligand engineering of tetra N-heterocyclic carbenes for boosting catalytic aziridination

Brett A. Smith, Somon Hakimov, David M. Jenkins, Konstantinos D. Vogiatzis

Research output: Contribution to journalArticlepeer-review

Abstract

A comprehensive computational study on the underlying reactivity of iron tetra-NHC complexes for C2 + N1 aziridination catalysis is presented. A library of 18 unique iron tetra-NHC complexes was constructed, and a computational screening was performed on the reaction barriers associated with the rate-determining step (formation of an open chain radical intermediate). Thermodynamic barriers were computed along with a variety of steric and electronic properties, including the percentage of buried volume, orbital energies and ETS-NOCV analysis, which were used to identify key characteristics related to reactivity. The analysis performed in this study successfully identified key differences in tetracarbenes, such as linking groups (BMe2 or CH2) and the identity of the NHC groups (imidazole, imidazoline or benzimidazole) in terms of sterics, electronics and thermodynamics. Additionally, we have proposed two reaction pathways based on electronic structure arguments for the formation of the key open-chain radical intermediate. The first reaction pathway proceeds through a σ-hole channel where the Fe(iv)-imide intermediate evolves into Fe(iii)-imidyl radical through electron donation into the antibonding σ* orbital, while the second involves a Fe(iii)-imidyl radical formed through a π-hole channel (donation into π*). These pathways are consistent with the isoelectronic iron(iv)-oxo species for hydrogen atom abstraction mechanisms and they can be used as descriptors of the rate-determining step of the aziridination reaction.

Original languageEnglish
Pages (from-to)14665-14677
Number of pages13
JournalDalton Transactions
Volume53
Issue number35
DOIs
StatePublished - Aug 2 2024

Funding

B. A. S., D. M. J., and K. D. V. are grateful to the NIH (R15GM117494-02) for financial support. This work was partially supported by the National Science Foundation under Grant CHE 2154697. Any opinions, findings, and conclusions expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The authors acknowledge the Infrastructure for Scientific Applications and Advanced Computing (ISAAC) of the University of Tennessee for computational resources.

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