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Record W2014552730 · doi:10.1103/physreve.71.041607

Modeling phase transitions during the crystallization of a multicomponent fat under shear

2005· article· en· W2014552730 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePhysical Review E · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsUniversity of GuelphUniversity of Waterloo
FundersU.S. Department of Energy
KeywordsCrystallizationCrystalliteCrystallographyShear ratePhysicsPhase transitionMaterials scienceShear (geology)Condensed matter physicsThermodynamicsChemistryRheologyComposite material

Abstract

fetched live from OpenAlex

The crystallization of multicomponent systems involves several competing physicochemical processes that depend on composition, temperature profiles, and shear rates applied. Research on these mechanisms is necessary in order to understand how natural materials form crystalline structures. Palm oil was crystallized in a Couette cell at 17 and $22\phantom{\rule{0.2em}{0ex}}\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$ under shear rates ranging from $0\phantom{\rule{0.3em}{0ex}}\text{to}\phantom{\rule{0.3em}{0ex}}2880\phantom{\rule{0.3em}{0ex}}{\mathrm{s}}^{\ensuremath{-}1}$ at a synchrotron beamline. Two-dimensional x-ray diffraction patterns were captured at short time intervals during the crystallization process. Radial analysis of these patterns showed shear-induced acceleration of the phase transition from $\ensuremath{\alpha}$ to ${\ensuremath{\beta}}^{\ensuremath{'}}$. This effect can be explained by a simple model where the $\ensuremath{\alpha}$ phase nucleates from the melt, a process which occurs independently of shear rate. The $\ensuremath{\alpha}$ phase grows according to an Avrami growth model. The ${\ensuremath{\beta}}^{\ensuremath{'}}$ phase nucleates on the $\ensuremath{\alpha}$ crystallites, with the amount of ${\ensuremath{\beta}}^{\ensuremath{'}}$ crystal formation dependent on the rate of transformation of $\ensuremath{\alpha}$ to ${\ensuremath{\beta}}^{\ensuremath{'}}$ as well as the growth rate of the ${\ensuremath{\beta}}^{\ensuremath{'}}$ phase from the melt. The shear induced $\ensuremath{\alpha}\text{\ensuremath{-}}{\ensuremath{\beta}}^{\ensuremath{'}}$ phase transition acceleration occurs because under shear, the $\ensuremath{\alpha}$ nuclei form many distinct small crystallites which can easily transform to the ${\ensuremath{\beta}}^{\ensuremath{'}}$ form, while at lower shear rates, the $\ensuremath{\alpha}$ nuclei tend to aggregate, thus retarding the nucleation of the ${\ensuremath{\beta}}^{\ensuremath{'}}$ crystals. The displacement of the diffraction peak positions revealed that increased shear rate promotes the crystallization of the higher melting fraction, affecting the composition of the crystallites. Crystalline orientation was observed only at shear rates above $180\phantom{\rule{0.3em}{0ex}}{\mathrm{s}}^{\ensuremath{-}1}$ at $17\phantom{\rule{0.2em}{0ex}}\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$ and $720\phantom{\rule{0.3em}{0ex}}{\mathrm{s}}^{\ensuremath{-}1}$ at $22\phantom{\rule{0.2em}{0ex}}\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.839
Threshold uncertainty score0.126

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 head0.031
GPT teacher head0.285
Teacher spread0.254 · 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