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Record W2579002727 · doi:10.32920/ryerson.14652342.v1

Encapsulation Through The Use Of Emulsified Microemulsions

2021· preprint· en· W2579002727 on OpenAlexafffund
Ruby Rafanan

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldChemistry
TopicSurfactants and Colloidal Systems
Canadian institutionsToronto Metropolitan University
FundersMcMaster UniversityAdvanced Foods and Materials Network
KeywordsMicroemulsionDifferential scanning calorimetrySmall-angle X-ray scatteringChemical engineeringMaterials scienceAqueous solutionPhase (matter)Aqueous two-phase systemChromatographyChemistryScatteringOrganic chemistryPulmonary surfactantThermodynamics

Abstract

fetched live from OpenAlex

Emulsified microemulsions (EMEs), first described in detail in 2005 by the group of Garti, consist of a thermodynamically stable water-in-oil microemulsion phase (w1/o) further dispersed within an aqueous continuous phase (w2). These internally-structured w1/o/w2 dispersions are promising controlled release vehicles for water-soluble flavouring compounds, drugs and nutraceuticals. With a stable internal droplet structure, storage stability is improved over non-thermodynamically stable structured emulsions and may exhibit unique controlled release behaviour. Use of food-grade components allows for wider and safer applications in food and pharmaceutical products. In this thesis, a food-grade w1/o microemulsion consisting of glycerol monooleate, tricaprylin and water was dispersed in an aqueous (w2) phase by membrane emulsification and stabilized by a caseinate-pectin complex to produce w1/o/w2 EMEs. The resulting EME showed no signs of phase separation for weeks at room temperature. The microemulsion and EME were characterized by differential scanning calorimetry (DSC), cryo-TEM and small angle x-ray scattering (SAXS) to determine whether the microemulsion’s internal structure was maintained after emulsification. It was shown that EME droplets displayed ordering around the periphery consistent with some loss of microemulsion structure, but maintained the characteristic disordered microemulsion structure at the droplet core. Overall, this research demonstrated the feasibility of developing EME for possible applications in food and non-food applications.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.199
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.101
GPT teacher head0.277
Teacher spread0.177 · 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.

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

Citations1
Published2021
Admission routes2
Has abstractyes

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