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Record W2937939913 · doi:10.1021/acsomega.9b00147

Heterogeneous Nucleation of 1,3-Distearoyl-2-oleoylglycerol on Tristearin Surfaces

2019· article· en· W2937939913 on OpenAlexafffund
Edmund D. Co, Saeed M. Ghazani, David A. Pink, Alejandro G. Marangoni

Bibliographic record

VenueACS Omega · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsSt. Francis Xavier UniversityUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCompute Canada
KeywordsNucleationKineticsSurface energyChemistryCritical radiusCrystallographyIsothermal processMaterials scienceActivation energyDifferential scanning calorimetryThermodynamicsChemical physicsChemical engineeringPhysical chemistryOrganic chemistrySPHERES

Abstract

fetched live from OpenAlex

The following work investigates the heterogeneous nucleation of 2-oleodistearin (SOS) triglycerides on surfaces formed by crystals of tristearin triglyceride (SSS). This work shows, through computer simulations and nucleation kinetics, that SOS may heterogeneously nucleate on SSS surfaces. Atomic-scale molecular dynamics showed that SOS molecules exhibited an affinity to a simulated SSS surface. Nucleation kinetics using differential scanning calorimetry showed that the inclusion of minor amounts of SSS (from 1 to 4%) in an SOS melt resulted in an increase in the isothermal nucleation rate of crystallizing SOS. Using a model based on the Fisher-Turnbull approach, estimates of the surface free energy, activation free energy, and the critical radius were calculated from the nucleation rates. The estimated parameters demonstrate the heterogeneous nucleation of SOS on SSS surfaces: reduced surface free energies, activation free energies, and critical radii with the inclusion of SSS in an SOS melt. This may point to strategies to enhance the nucleation of one of the three major triglycerides present in cocoa butter and the one that crystallizes first from the melt for better control of the chocolate tempering process.

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 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 score0.072
Threshold uncertainty score0.299

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 science0.0000.000
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 head0.011
GPT teacher head0.197
Teacher spread0.186 · 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

Citations19
Published2019
Admission routes2
Has abstractyes

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