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Record W2334686119 · doi:10.1021/ie1025985

Crystal Morphology of Hydrogenated Castor Oil in the Crystallization of Oil-in-Water Emulsions: Part I. Effect of Temperature

2011· article· en· W2334686119 on OpenAlexaff
Dingzheng Yang, Andrew N. Hrymak

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsWestern UniversityMcMaster University
Fundersnot available
KeywordsCrystallizationNucleationDifferential scanning calorimetrySupercoolingMaterials scienceCrystal (programming language)CrystallographyScanning electron microscopeOptical microscopePolarized light microscopyMorphology (biology)Chemical engineeringChemistryThermodynamicsComposite materialOrganic chemistryOptics

Abstract

fetched live from OpenAlex

Crystallization of hydrogenated castor oil-in-water emulsions has been studied by polarized light microscopy, scanning electron microscopy, X-ray powder diffraction, and differential scanning calorimetry. Three types of crystal morphologies have been observed: rosettes, fibers, and irregular crystals. The energy barrier to nucleation for fibers is suggested to be higher than that of rosettes. Irregular crystals are thermodynamically less stable and tend to transform into stable polymorphs. Under isothermal crystallization at a temperature of 70 °C, mainly rosettes are observed. With an increase of supercooling, by decreasing the temperature to 55 °C, more fibers form due to a lower energy barrier to nucleation. If the crystallization temperature is set to 45 °C, irregular crystals form first and then transform into rosettes. A nonisothermal crystallization study shows that at a cooling rate of 1 °C/min, more rosettes and fibers are produced compared to a higher cooling rate of 5 °C/min, which produces more irregular crystals.

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 score0.001
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.059
GPT teacher head0.263
Teacher spread0.203 · 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

Citations31
Published2011
Admission routes1
Has abstractyes

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