Edible fat structures at high solid fat concentrations: Evidence for the existence of oil-filled nanospaces
Bibliographic record
Abstract
We have characterized the surfaces of grain boundaries in edible oils with high solid fat content by combining ultra-small angle x-ray scattering (USAXS) with theoretical modelling and computer simulation. Our results will lead to understand the solid structures formed at the time of manufacturing fats like confectionery fats as well as pave the way for the engineering of innovative fat products. Edible fats are complex semi-solid materials where a solid structure entraps liquid oil. It was not until USAXS combined with modelling was used that the nano- to meso-structures for systems with less than 20% solids were understood. The interpretation of those results utilized models of crystalline nanoplatelets represented by rigid close-packed flat aggregates made of spheres and was allowed to aggregate using the Metropolis Monte Carlo technique. Here, we report on systems containing between 50% and 90% solids. We modelled the solid phase as being formed from seeds onto which solids condensed thereby giving rise to oil-filled nanospaces. The models predicted that the system (a) exhibits structures with fractal dimensions approximately 2, (b) a broad peak somewhat masking that slope, and (c) for smaller values of q, indications that the structures with fractal dimension approximately 2 are uniformly distributed in space. The interpretation of the experimental data was completely driven by these results. The computer simulation predictions were used in conjunction with the USAXS observations to conclude that the systems studied scattered from oil-cavities with sizes between ∼800 and ∼16 000 Å and possessed rough 2-dimensional walls.
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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 | 0.000 |
| 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 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".