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Record W2438160755 · doi:10.1002/cphc.201501190

Effect of Confinement on the Properties of Sequestered Mixed Polar Solvents: Enzymatic Catalysis in Nonaqueous 1,4‐Bis‐2‐ethylhexylsulfosuccinate Reverse Micelles

2016· article· en· W2438160755 on OpenAlexaff
Andrés M. Durantini, R. Darío Falcone, Juana J. Silber, N. Mariano Correa

Bibliographic record

VenueChemPhysChem · 2016
Typearticle
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsMcGill University
FundersAgencia Nacional de Promoción Científica y TecnológicaConsejo Nacional de Investigaciones Científicas y TécnicasAgencia Córdoba Ciencia
KeywordsChemistryMicelleSolventNanoreactorDimethylformamideSubstrate (aquarium)CatalysisPolarFormamideSolvent effectsChemical engineeringOrganic chemistryAqueous solution

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.586

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.215
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2016
Admission routes1
Has abstractyes

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