Inner-Sphere Activation, Outer-Sphere Catalysis: Theoretical Study on the Mechanism of Transfer Hydrogenation of Ketones Using Iron(II) PNNP Eneamido Complexes
Bibliographic record
Abstract
We have studied the mechanism of transfer hydrogenation (TH) in silico using density functional theory (DFT) with the Fe(II) PNNP bis(eneamido) model complexesFe(CO)(H 2 PCH═CHNCH 2 CH 2 NCH═CHPH 2 ) based on compounds with the general formula Fe(CO)(R 2 PCH═CHN(( S, S )-CH(R′)CH(R′))NCH═CHPR 2 ) (R, R′ = alkyl, aryl). An initial activation period involving 1 equiv of isopropyl alcohol reduces the bis(eneamido) complex by a stepwise inner-sphere mechanism. This activation step is proposed to be slow because of the high barrier calculated for the inner-sphere transfer of hydride to an imine carbon on the ligand. This bis(eneamido) complex reacts with isopropyl alcohol to produce the active species, proposed to be the unsymmetrical amido-eneamido complex Fe(CO)(H 2 PCH 2 CH 2 NCH 2 CH 2 NCH═CHPH 2 ), which is within the catalytic cycle. The catalytic cycle propagates by addition of isopropyl alcohol to the Fe–amido half of the ligand to generate an FeH–NH unit. However, a stepwise outer-sphere mechanism has been calculated to transfer the proton and hydride in two discrete steps which are connected through a ground state involving an NH-stabilized alkoxide ion. The highest calculated barrier is hydride transfer in the activation period, while the second highest barrier involves hydride transfer during the catalytic cycle. The resting states during catalysis are the alkoxide complex Fe(CO)(O i Pr)(H 2 PCH 2 CH 2 NHCH 2 CH 2 NCH═CHPH 2 ) and/or the amino–hydrido complex FeH(CO)(H 2 PCH 2 CH 2 NHCH 2 CH 2 NCH═CHPH 2 ), on the basis of their low relative free energies. Calculated kinetic isotope effect values are in rough agreement with the experimentally determined values, which also supports the proposed mechanism of catalysis. This data complements the experimental work recently published by our group ( J. Am. Chem. Soc. 2012, 134, 12266−12280) and leads to a deeper understanding of how these highly active “green” catalysts operate under catalytic conditions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.004 | 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".