Structure and Physical Properties of Plant Wax Crystal Networks and Their Relationship to Oil Binding Capacity
Bibliographic record
Abstract
Abstract The microstructure, melting and crystallization behavior, rheological properties and oil binding capacity of crystalline networks of plant‐derived waxes in edible oil were studied and then compared amongst different wax types. The critical concentrations for oleogelation of canola oil by rice bran wax (RBX), sunflower wax, candelilla wax, and carnauba wax were 1, 1, 2, and 4 %, respectively, suggesting RBX and sunflower wax are more efficient structurants. A phenomenological two‐phase exponential decay model was implemented to quantify the oil‐binding capacity of these oleogels. Parameters obtained from this empirical model were then evaluated against microscale structural attributes such as crystal size, mass distribution and porosity to determine the structural dependence of oil‐binding capacity. Gels containing candelilla wax exhibited the greatest oil‐binding capacity, as they retained nearly 90 % of their oil. This is due to the small crystal size as well as the spatial distribution of these crystals. Using a microscopic to macroscopic approach, this study examines how the structural characteristics unique to each wax and resulting oleogel system affect functionality and macroscopic behavior.
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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".