Shear-induced aggregation or disaggregation in edible oils: Models, computer simulation, and USAXS measurements
Bibliographic record
Abstract
The effects of shear upon the aggregation of solid objects formed from solid triacylglycerols (TAGs) immersed in liquid TAG oils were modeled using Dissipative Particle Dynamics (DPD) and the predictions compared to experimental data using Ultra-Small Angle X-ray Scattering (USAXS). The solid components were represented by spheres interacting via attractive van der Waals forces and short range repulsive forces. A velocity was applied to the liquid particles nearest to the boundary, and Lees-Edwards boundary conditions were used to transmit this motion to non-boundary layers via dissipative interactions. The shear was created through the dissipative forces acting between liquid particles. Translational diffusion was simulated, and the Stokes-Einstein equation was used to relate DPD length and time scales to SI units for comparison with USAXS results. The SI values depended on how large the spherical particles were (250 nm vs. 25 nm). Aggregation was studied by (a) computing the Structure Function and (b) quantifying the number of pairs of solid spheres formed. Solid aggregation was found to be enhanced by low shear rates. As the shear rate was increased, a transition shear region was manifested in which aggregation was inhibited and shear banding was observed. Aggregation was inhibited, and eventually eliminated, by further increases in the shear rate. The magnitude of the transition region shear, γ̇t, depended on the size of the solid particles, which was confirmed experimentally.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".