Effect of the Structure of the Diamine Backbone of P−N−N−P ligands in Iron(II) Complexes on Catalytic Activity in the Transfer Hydrogenation of Acetophenone
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The asymmetric transfer hydrogenation of aromatic ketones can be efficiently accomplished using catalysts that are based on platinum group metals which are more toxic and less abundant than iron. For that reason the discovery of iron based catalysts for the use in this transformation is important. To address this issue, we synthesized a new series of iron(II)-based precatalysts trans-[Fe(Br)(CO)(PPh(2)CH(2)CH═NCHRCHRN═CHCH(2)PPh(2))]BPh(4) (5a-5d) containing P-N-N-P ligands with the diamines (R,R)-1,2-diaminocyclohexane (a), (R,R)-1,2-diphenyl-1,2-diaminoethane (b), (R,R)-1,2-di(4-methoxyphenyl)-1,2-diaminoethane (c), and ethylenediamine (d) incorporated in the backbone using a convenient one-pot synthesis using readily available starting materials. All of the complexes, when activated with a base, show a very high activity in the transfer hydrogenation catalysis of acetophenone, using 2-propanol as a reducing agent under mild conditions. A comparison of the TOF of complexes 5a-5d show that the catalytic activity of complexes increase as the size of the substituents in the backbone of ligands increases (d < a < b = c).
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.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it