Effect of Confinement on the Properties of Sequestered Mixed Polar Solvents: Enzymatic Catalysis in Nonaqueous 1,4‐Bis‐2‐ethylhexylsulfosuccinate Reverse Micelles
Bibliographic record
Abstract
The influence of different glycerol, N,N-dimethylformamide (DMF) and water mixtures encapsulated in 1,4-bis-2-ethylhexylsulfosuccinate (AOT)/n-heptane reverse micelles (RMs) on the enzymatic hydrolysis of 2-naphthyl acetate by α-chymotrypsin is demonstrated. In the case of the mixtures with DMF and protic solvents it has been previously shown, using absorption, emission and dynamic light-scattering techniques, that solvents are segregated inside the polar core of the RMs. Protic solvents anchor to the AOT, whereas DMF locates to the polar core of the aggregate. Thus, DMF not only helps to solubilize the hydrophobic substrate, increasing its effective concentrations but surprisingly, it does not affect the enzyme activity. The importance of ensuring the presence of RMs, encapsulation of the polar solvents and the corrections by substrate partitioning in order to obtain reliable conclusions is highlighted. Moreover, the effect of a constrained environment on solvent-solvent interactions in homogenous media and its impact on the use of RMs as nanoreactors is stressed.
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.
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) | 0.000 | 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 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".