Dynamic Kinetic Resolution of Secondary Alcohols Combining Enzyme‐Catalyzed Transesterification and Zeolite‐Catalyzed Racemization
Bibliographic record
Abstract
Hydrophobic zeolite beta containing low concentrations of Zr or Al was found to be a good catalyst for the racemization of 1-phenylethanol. The formation of styrene as a side product could be minimized by reducing the metal concentration in the zeolite beta. Combined with an immobilized lipase from Candida antarctica, the dynamic kinetic resolution of 1-phenylethanol to the (R)-phenylethylester can be achieved with high yield and selectivity. The reaction was best conducted in toluene as solvent at 60 degrees C, with higher temperatures leading to a loss in the enantioselectivity of the formed ester. By using high-molecular-weight acyl-transfer reagents, such as vinyl butyrate or vinyl octanoate, a high enantiomeric excess of the product esters of 92 and 98 %, respectively, could be achieved. This is attributed to a steric effect: the bulky ester is less able to enter the pore space of the zeolite catalyst where the active sites for racemization are localized. Close to 100 % conversion of the alcohol was achieved within 2 h. If the more common acyl donor, isopropenyl acetate, was used, the enantiomeric excess (ee) of the formed ester was only 67 %, and the reaction was considerably slower.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
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".