Synthesis of Iron P-N-P′ and P-NH-P′ Asymmetric Hydrogenation Catalysts
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Complexes of the type mer, trans -[Fe(P-N-P′)(CO) 2 Br]BF 4 are known to be precatalysts for the asymmetric direct hydrogenation of ketones and imines. Employing related ligand scaffolds, we successfully generated and tested the series of three new precatalysts [Fe(PCy 2 CH 2 CH═NCH(R)CH 2 PPh 2 )(CO) 2 Br]BF 4 with chirality derived from ( S )-amino alcohols with phenyl, benzyl, and isopropyl substituents (R), yielding fairly active and selective systems. For the reduction of acetophenone to ( S )-1-phenylethanol turnover frequencies up to 920 h –1 and up to 74% enantiomeric excess at 50 °C and 5–25 atm of H 2 were obtained. We found, however, that placing these large groups R next to nitrogen was found to be deleterious to catalytic activity. Extending the scope of the ligand structure, we then developed a series of six P-N-P and five P-NH-P′ systems starting with o -diphenylphosphinobenzaldehyde and the phosphine-amines PPh 2 CHR 1 CHR 2 NH 2 (R 1 = H, Ph, CH 2 Ph, iPr with R 2 = H or R 1 = Me, Ph with R 2 = Ph) as well as their corresponding [Fe(P-N-P′)(NCMe) 3 ][BF 4 ] 2 and [Fe(P-NH-P′)(NCMe) 3 ][BF 4 ] 2 complexes, which were not catalytically active. Finally, we made the new achiral iron complex mer, cis -Fe(PPh 2 ( o -C 6 H 4 )CHNCH 2 CH 2 PPh 2 )(CO)Br 2, which was active for the direct hydrogenation of acetophenone, achieving turnover frequencies of 800 h –1 at 50 °C and 25 atm of H 2 .
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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 | 0.001 |
| 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) | 0.000 | 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".