Water content influences the selectivity of CALB-catalyzed kinetic resolution of phenoxymethyl-substituted secondary alcohols
Bibliographic record
Abstract
Derivatives of 1-phenoxy-2-alkanols were kinetically resolved by esterification with irreversible and reversible acyl donors using lipase B from Candida antarctica (Novozyme 435) as a catalyst. To optimize the relative rate of reaction (the E-value), esterifications in eight different solvents with different water activities were performed. For 3-bromo-1-phenoxy-2-propanol (1), the E-values in all the solvents were higher when the water activity was increased, while the E-values for 1-phenoxy-2-pentanol (2) and 3-chloro-1-phenoxy-2-propanol (3) decreased by increasing water activity. The water content of the various reaction media with the same water activity was determined. Solvents such as 1,4-dioxane, acetonitrile, and tetrahydrofuran contained much more water than hexane, carbon tetrachloride, cyclohexane, toluene, and benzene. At high-water activity, the high-water content of the former group of solvents resulted in termination of the reaction at low conversion. The reason seemed to be that the acyl donor and possibly also the produced esters were hydrolyzed. This was not the case when the esterification was performed in water-immiscible solvents with the same water activity.Key words: kinetic resolution, E-value, solvents, water activity, water content.
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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".