Hardness, plasticity, and oil binding capacity of binary mixtures of natural waxes in olive oil
Bibliographic record
Abstract
In this study, olive oil oleogels structured with less than 4% binary blends of sunflower wax (SFW), rice bran wax (RBW), candelilla wax (CDW), and beeswax (BW) were characterized. Among the different binary wax oleogels, samples structured with 3% (w/w) of binary mixtures of SFW and RBW, as well as binary mixtures of CDW and BW, displayed a high oil binding capacity relative to any other mixtures. Moreover, in some binary wax oleogels, back extrusion hardness and elastic constant were significantly higher than that of oleogels prepared using the individual waxes. This was interpreted as a synergism between these waxes. Image analysis of oleogel brightfield micrographs indicated that the samples with a higher elastic constant had a lower box-counting fractal dimension and larger crystals, suggesting that this increase in the elastic constant was a consequence of the lower fractal dimension of the wax crystal network, in agreement with established fractal structural-mechanical models for van der Waals colloidal networks. The crystal structure of the individual waxes and their blends showed orthorhombic perpendicular subcell packing arrangements, which did not change upon mixing, suggesting this length scale did not play a role in the observed synergism. The melting point of binary mixtures of waxes in olive oil was in the range of 43.2 °C to 67.4 °C and pseudo-ideal mixing behavior was observed. The hardness and plasticity (brittleness) of the 2% and 3% binary wax mixtures in olive oil characterized using back extrusion, were similar to those of a commercial soft margarine, suggesting a potential use of the wax oleogels as margarine or spread replacers.
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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".