Mechanistic Insights into Fe Catalyzed α‐C−H Oxidations of Tertiary Amines
Bibliographic record
Abstract
Abstract We report detailed mechanistic investigations of an iron‐based catalyst system, which allows the α‐C−H oxidation of a wide variety of amines. In contrast to other catalysts that effect α‐C−H oxidations of tertiary amines, the system under investigation exclusively employs peroxy esters as oxidants. More common oxidants (e. g. t BuOOH) previously reported to affect amine oxidations via free radical pathways do not provide amine α‐C−H oxidation products in combination with the described catalyst system. The investigations described herein employ initial rate kinetics, kinetic profiling, DFT calculations as well as Eyring, kinetic isotope effect, Hammett, ligand coordination, and EPR studies to shed light on the Fe catalyst system. The obtained data suggest that the catalytic mechanism proceeds through C−H abstraction at a coordinated substrate molecule. This rate‐determining step occurs either through an Fe(IV) oxo pathway or a 2‐electron pathway at an Fe(II) intermediate with bound oxidant. DFT calculations indicate that the Fe(IV) oxo mechanism will be the preferred route of these two possibilities. We further show via kinetic profiling and EPR studies that catalyst activation follows a radical pathway, which is initiated by hydrolysis of PhCO 3 t Bu to t BuOOH. Overall, the obtained mechanistic data support a non‐classical, Fe catalyzed pathway that requires substrate binding, inducing selectivity for α‐C−H functionalization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".