Laminar Shear Effects on Crystalline Alignments and Nanostructure of a Triacylglycerol Crystal Network
Bibliographic record
Abstract
The effects of laminar shear on crystalline orientation and the nanostructure of triglyceride crystal networks were quantified by using different microscopic techniques. Cocoa butter (CB) was crystallized in the presence and absence of an external shear field. Two different dynamic samples were crystallized under a shear rate of approximately 340s –1 by using a continuous Couette-type laminar shear crystallizer and by using a standard paddle mixer. To improve imaging resolution, liquid oil was removed from crystallized samples using isobutanol and aqueous solutions of different surfactants such as AOT, Teepol, and Fatsolve. Using cryogenic scanning electron microscopy (Cryo-SEM), oriented sheets of crystalline cocoa butter were observed in the sample obtained in the laminar shear crystallizer, while spherulitic structures were observed in the statically crystallized sample. The strong influence of the applied laminar shear on the nanoscale structure is demonstrated by characterization of CB platelet size using cryogenic transmission electron microscopy (Cryo-TEM). Shear crystallization caused a reduction in the platelets’ length from 2000 to 300 nm and width from 165 to 130 nm. The platelets’ thickness, obtained from Scherrer analysis of the 002 SAXS reflection, yielded a domain size of 54.8 nm for the specimen crystallized under laminar shear and 58.2 nm for the statically crystallized sample. This work demonstrates the large effects of shear during the crystallization process on the microstructure of polycrystalline materials.
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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 | 0.000 |
| 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".