Asymmetric Transfer Hydrogenation of Ketones Using New Iron(II) (P‐NH‐N‐P′) Catalysts: Changing the Steric and Electronic Properties at Phosphorus P′
Bibliographic record
Abstract
Abstract The asymmetric transfer hydrogenation (ATH) of ketones is an efficient method for producing enantio‐enriched alcohols which are used as intermediates in a variety of industrial processes. Here we report the synthesis of new iron ATH precatalysts (S,S)‐[FeBr(CO)(Ph2PCH2CH2NHCHPhCHPhNC=CHCH2PR′2)][BPh4] (R′=Et, and ortho‐tolyl (o‐Tol)) where one of the phosphine groups is modified with small alkyl and large aryl substituents to probe the effect of this change on the activity and selectivity of the catalytic system. A simple reversible equilibrium kinetic model is used to obtain the initial TOF and the inherent enantioselectivity S=kR/kS of these catalysts along with those for the previously reported catalysts with R′=Ph and Cy for the ATH of acetophenone. With an increase in the size of the PR′2 group, the TOF goes through a maximum at PPh2 while the S value goes through a maximum of 510 at R′=Cy. The complex with R′=o‐Tol starts with a high S value of 200 but is rapidly changed to a second catalyst with an S value of 28. For the reduction of acetophenone to (R)‐1‐phenylethanol, turnover numbers of up to 5200 and ee up to 98 % were achieved. The chemotherapeutic pharmaceutical precursor (R)‐(3′,5′‐bis(trifluoromethyl))‐1‐phenylethanol is synthesized in up to 95 % ee. Several other alcohols can be prepared in greater than 90 % ee by choosing the precatalyst with the correctly matched steric properties. A hydride complex derived from the catalyst with R′=Cy is characterized by NMR spectroscopy. It is proposed that low concentration trans‐hydride carbonyl complexes with the FeH parallel to the NH of the ligand are the active catalysts in all of these systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".