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Record W1976285117 · doi:10.1021/cg050467r

A Conceptual Model for Shear-Induced Phase Behavior in Crystallizing Cocoa Butter

2007· article· en· W1976285117 on OpenAlexaff
Gianfranco Mazzanti, Sarah Guthrie, Alejandro G. Marangoni, Stefan H. J. Idziak

Bibliographic record

VenueCrystal Growth & Design · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsUniversity of GuelphUniversity of Waterloo
Fundersnot available
KeywordsCrystalliteNucleationLamellar structureShear (geology)Materials scienceCrystallizationShear matrixDiffractionThermodynamicsCrystallographyShear ratePhase (matter)Phase transitionMineralogyChemical physicsChemistryComposite materialRheologyOpticsPhysicsAmorphous solidOrganic chemistry

Abstract

fetched live from OpenAlex

We propose a conceptual model to explain the quantitative data from synchrotron X-ray diffraction experiments on the shear-induced phase behavior of cocoa butter, the main structural component of chocolate. We captured two-dimensional diffraction patterns from cocoa butter at crystallization temperatures of 17.5, 20.0, and 22.5 °C under shear rates from 45 to 1440 s -1 and under static conditions. From the simultaneous analysis of the integrated intensity, correlation length, lamellar thickness, and crystalline orientation, we postulate a conceptual model to provide an explanation for the distribution of phases II, IV, V, and X and the kinetics of the process. As previously proposed in the literature, we assume that the crystallites grow layer upon layer of slightly different composition. The shear rate and temperature applied define these compositions. Simultaneously, the shear and temperature define the crystalline interface area available for secondary nucleation by promoting segregation and affecting the size distribution of the crystallites. The combination of these factors (composition, area, and size distribution) favors dramatically the early onset of phase V under shear and determines the proportions of phases II, IV, V, and X after the transition. The experimental observations, the methodology used, and the proposed explanation are of fundamental and industrial interest, since the structural properties of crystalline networks are determined by their microstructure and polymorphic crystalline state. Different proportions of the phases will thus result in different characteristics of the final material.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.003
Scholarly communication0.0020.005
Open science0.0040.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.080
GPT teacher head0.286
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations37
Published2007
Admission routes1
Has abstractyes

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