Iron(II) Complexes for the Efficient Catalytic Asymmetric Transfer Hydrogenation of Ketones
Bibliographic record
Abstract
Abstract Ferrous efficiency: New achiral and chiral iron complexes containing P‐N‐N‐P diiminodiphosphine ligands display high activity—and in the case of the catalyst shown, high enantioselectivity—in the catalytic transfer hydrogenation of ketones. This is an important step in the journey to replace precious and toxic platinum metal catalysts with cheap and environmentally friendly iron compounds. magnified image Iron(II) carbonyl compounds of the type trans‐[Fe(NCMe)(CO)(P‐N‐N‐P)][BF4]2 bearing the ethylenediamine‐derived diiminodiphosphine ligands (R,R)‐ or (S,S)‐1,2‐diphenyl‐1,2‐diaminoethane were synthesized and characterized, including by their crystal structures. The new complexes are suitable precatalysts for the transfer hydrogenation of ketones at room temperature, giving turnover frequencies of up to 2600 h−1 with low catalyst loadings (0.025–0.17 %). Screening experiments showed that the precatalysts are able to produce alcohols from a wide range of simple ketones. For sterically demanding prochiral ketones, excellent enantioselectivities were obtained (up to 96 % ee).
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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".