Crystallization, Polymorphism, and Binary Phase Behavior of Model Enantiopure and Racemic Triacylglycerols
Bibliographic record
Abstract
Triacylglycerols (TAG) are the main component in fats and oils and a major component in many food and consumer products. These compounds are always asymmetric (about the sn- 2position), while many diacid and all triacid TAG are chiral. To understand what effect this has on their crystallization behavior, model enantiopure (1,2-bisdecanoyl-3-palmitoyl- sn -glycerol) and racemic (bisdecanoyl-1(3)-palmitoyl- rac -glycerol) TAG were prepared and characterized. In addition, a binary phase diagram was prepared to investigate their phase behavior and the racemate’s crystalline tendency. For the subject compounds, infrared spectroscopy and X-ray powder diffraction data indicate the enantiopure TAG is β′-stable, whereas the racemic mixture is β-stable. In addition, based on the phase diagram, the high-melting form of the racemic mixture is a racemic compound (with a unit cell containing equal quantities of both enantiomers). Racemic (and near-racemic) mixtures also crystallize in a lower-melting metastable conglomerate β′ form. Thus, there are critical differences between the crystallization behavior of enantiopure and racemic TAG, and future investigations of these compounds should reflect these findings.
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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".