A Mechanistic Investigation of the Asymmetric Meerwein−Schmidt−Ponndorf−Verley Reduction Catalyzed by BINOL/AlMe<sub>3</sub>Structure, Kinetics, and Enantioselectivity
Bibliographic record
Abstract
The kinetics of the Al-catalyzed asymmetric Meerwein-Schmidt-Ponndorf-Verley (MSPV) reduction are presented. Structural identification of the catalytic precursor formed in situ between (S)-2,2'-dihydroxy-1,1'-binapthyl ((S)-BINOL), AlMe3, and 2-propanol was established through 1H and 27Al NMR spectroscopies, and APCIMS. All experimental evidence points toward the formation of a BINOL-chelated, pentacoordinate aluminum species in solution. Ligand-accelerated catalysis was confirmed for the phenolate/AlMe3/2-propanol system. The rate law for the catalytic reaction was determined to be nearly unimolecular dependent on aluminum, zero-order dependent on substrate, and inversely dependent on 2-propanol. At the low catalyst loading employed in the BINOL/AlMe3 system, the inherent reversibility of the MSPV reaction does not affect product yield or enantiomeric excess over time. Systematic ligand studies imply that while a tetrahedral geometry around the aluminum center may result in the most active MSPV reduction catalysts, the enantioselectivity of the reaction is enhanced when the aluminum center allows for a 2-point coordination of the substrate to achieve a pentacoordinate geometry with the fifth ligand weakly coordinated to the axial site of a pseudo square pyramid.
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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 | 0.001 |
| 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".