Synthesis and Physical Properties of Triacylglycerol Oligomers: Examining the Physical Functionality Potential of Self-Metathesized Highly Unsaturated Vegetable Oils
Bibliographic record
Abstract
Seven model oligomers (from dimer to octamer) of the triacylglycerol (TAG) triolein were synthesized from oleic acid and fully characterized by 1 H NMR, 13 C NMR, mass spectroscopy, and gel permeation chromatography (GPC). The thermal stability of the oligomers as determined by TGA was excellent, with degradation beginning at 342 °C for the most thermally labile samples. The samples all presented glass transitions at low temperatures, with T g continuously shifting to higher temperatures with increasing numbers of monomers. The crystallization and melting behavior scaled with molecular size and relative number of double bonds in the trans- configuration. Flow behavior was investigated over a large range of temperatures (−10 to 110 °C), and application of the Herschel–Bulkey model to shear stress versus shear rate data evidenced a flow behavior dependent on molecular size and temperature. The oligomers presented a thinning to Newtonian flow transition temperature proportional to molecular size. The viscosity versus temperature data, fitted with a generalized van Velzen equation, suggested that it is the competition between the trans- character and size of the molecules which determines the rheology of these molecules. Overall, all the investigated properties plateaued at the hexamer, suggesting that no further marginal utility can be obtained with larger oligomers.
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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) | 0.000 | 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 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".