Modeling phase transitions during the crystallization of a multicomponent fat under shear
Bibliographic record
Abstract
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 $22\phantom{\rule{0.2em}{0ex}}\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".