Structure and properties of an ethylcellulose and stearyl alcohol/stearic acid (EC/SO:SA) hybrid oleogelator system
Bibliographic record
Abstract
The physical properties of stearyl alcohol:stearic acid (SO:SA) oleogels at varying oleogelator mass ratios were characterized in the presence of the polymer oleogelator ethylcellulose (EC). The large deformation properties of the combined EC/SO:SA oleogels at intermediate ratios (8:2 to 4:6) were similar to that of the corresponding SO:SA formulations. The remaining ratios exhibited a substantial increase in gel strength in the presence of EC, with the hardest composed of stearic acid (0:10). Neither polymorphism, nor thermal behavior of SO:SA were affected by EC, but increases in SFC at 10°C were correlated to harder gels. EC drastically altered the microstructure of the SOSA network producing structures made up of clusters of branching, needle‐like crystals. Overall, the increase in gel strength outside the ratios where pure stearyl alcohol or stearic acid crystals were present, could be attributed to increased solids and reinforcement by the secondary EC network. Practical applications: The hybrid gelator system investigated here has potential as fat mimetic. The SO:SA ratios which provided the greatest oil‐structuring ability and plasticity were 8:2 and 7:3 SO:SA. This strategy of using complementary gelators should prove useful for optimizing the functionality of oleogels for diverse food applications. Ethylcellulose improved the gelling efficiency and gel strength of the stearoyl alcohol/stearic acid oleogelator system by altering the crystalline microstructure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".