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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".