Critical laminar shear-temperature effects on the nano- and mesoscale structure of a model fat and its relationship to oil binding and rheological properties
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Bibliographic record
Abstract
This article reports on the effect of laminar shear on structural and mechanical properties of physical mixtures of fully hydrogenated soybean oil (FHSO) in soybean oil (SO). Blends were crystallized statically and under laminar shear rates of 30 and 240 s(-1) at different wall temperatures (-10, 0, 20 degrees C). The micro- and nanocrystalline structures were characterized using Polarized Light Microscopy (PLM), and Cryogenic Transmission Electron Microscopy (Cryo-TEM). Rheological analysis was used to determine changes in mechanical properties. Oil-binding capacity was analyzed through the measurement of the oil lost from the fat samples (OL). Shearing greatly affected the structure at the nano- and mesoscale. At low shear rates, blends displayed the largest increase in crystal size with an increase in wall temperature at both the nano- and mesoscale. On the other hand, at shear rates of 240 s(-1), the effect of crystallization temperature was observed only at the nanoscale since no changes in meso-crystal sizes were observed at different temperatures. Crystallization under laminar shear promoted the growth of spherical crystalline particles at the mesoscale, called here "solid-lipid meso-particles". Crystallization under higher shear rates led to the formation of a weak network with low oil-binding capacity and promoted the asymmetric growth of nanoplatelets. In statically crystallized blends, nanoplatelets had an aspect ratio of -2, while in sheared blends this value increased significantly. These results revealed the existence of critical shear rate values above which strong alterations in the structure of the solid crystalline network took place. Shearing also affected the material's strength. Laminar shear induced a decrease in elastic modulus and yield stress values which was more pronounced at higher shear rate-temperature combinations. Shear-temperature combinations were successfully used to structure fats at the nano and mesoscale.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it