Elucidation of Kinetic and Symmetry Effects on the Viscosity and Flow Behavior of Stearic and Oleic Triacylglycerols
Bibliographic record
Abstract
Abstract The flow behavior and viscosity of TAGs containing oleic and stearic acids were examined in the liquid phase as well as at temperatures close to the onset of crystallization by means of a temperature‐controlled rheometer. Gelling and crystallization transitions were unambiguously identified by singularities in the viscosity versus temperature curves of the TAGs. An additional transition between the gelling and onset of crystallization temperatures, attributed to the reorganization of the gel, was observed in the symmetrical TAGs only. The effect of the cooling rate, ranging between 0.1 and 5 °C/min, was investigated. The flow behavior of the studied TAGs was shown to be strongly determined by structural parameters (symmetry, degree of unsaturation). The flow behavior was also affected significantly by the cooling rate, suggesting that to certain extents the flow behavior determined by structural parameters could be changed by manipulating the cooling rate. The study confirmed that TAG crystallization is initiated by and depends, at least in part, on complex molecular short range order transformations occurring in the melt. The findings of the study may be valuable for evaluating systems and equipment that are involved in the storage, handling and processing of materials incorporating these TAGs.
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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 | 0.001 |
| 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".