Toward Iron‐Catalyzed Alkene Metathesis: Mapping the Reactivity and Deactivation Pathways of an Iron Metallacyclobutane
Bibliographic record
Abstract
Abstract Iron‐catalyzed alkene metathesis holds great promise as a sustainable alternative to its precious metal congeners, yet its development has been hindered by poor mechanistic understanding and rapid catalyst deactivation. Here, we report the combined computational and experimental identification of β‐hydride elimination as a key decomposition pathway from an iron metallacyclobutane, an essential intermediate in metathesis catalysis. Using our previously reported PC NHC P‐ligated iron(0) complex [(PC NHC P)Fe(N 2 ) 2 ], we observe under metathesis conditions the formation of an iron(II) allyl hydride product, consistent with our computational predictions of a low‐energy β‐hydride elimination pathway. Detailed spin‐state‐resolved DFT analysis reveals that while metallacyclobutane formation is feasible across multiple spin surfaces, subsequent reactivity is strongly governed by the singlet state. Coordination of N 2 is shown to inhibit metathesis and promote decomposition by raising the transition‐state barrier for cycloreversion while facilitating β‐hydride elimination. Subsequent calculations show that upon suppressing this decomposition channel productive metathesis is restored. These findings offer mechanistically grounded design principles for next‐generation iron‐based metathesis catalysts and highlight the importance of spin‐state control, ligand environment, and substrate selection in overcoming catalyst deactivation and provide a foray into productive iron catalyzed alkene metathesis.
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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 | 0.001 | 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 | 0.000 | 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".