Investigation of the interaction between a novel unnatural chiral ligand and reactant on palladium for asymmetric hydrogenation
Bibliographic record
Abstract
We report about the mechanistic studies of the reaction between a newly synthesized (S)-2-((R)-3H-dinaphtho[2,1-c:1',2'-e]azepin-4(5H)-yl)-2-phenylethanol based on the binaphthyl skeleton and (E)-2-methyl-5-phenylpent-2-enoic acid for the asymmetric hydrogenation of α,β-unsaturated acids with heterogeneous palladium catalysts. The specific interactions between the chiral ligand and reactant were investigated in solution with palladium nanoparticles, as well as under ultrahigh vacuum (UHV) conditions on the palladium metal surface in the absence of hydrogen. The reactions were explored using nuclear magnetic resonance (NMR) spectroscopy, scanning tunneling microscopy (STM), and high-resolution photoemission spectroscopy (HRPES) combined with density functional theory (DFT) calculations. A NMR study identified the interaction between both molecules with palladium nanoparticles in solution. In addition, STM and HRPES studies revealed the spatial distribution and configuration of both compounds on the palladium metal surface under UHV conditions. The theoretical results support the experimental results with respect to the interaction energy value. It was found that the reaction between the ligand and reactant occurs with hydrogen bonding on palladium surface, simultaneously. The present study provides mechanistic details of the asymmetric hydrogenation reaction, which bears a correlation between the ligand, reactant, and catalyst during the reaction.
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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".