Crystallization, Polymorphism, and Binary Phase Behavior of Model Enantiopure and Racemic 1,3-Diacylglycerols
Bibliographic record
Abstract
1,3-Diacylglycerols (1,3-DAG) are components in many natural, commercial, and food systems. These compounds are always asymmetric, and diacid forms are chiral. To understand what effect this has on their crystallization behavior, model enantiopure (1-decanoyl-3-palmitoyl- sn -glycerol) and racemic (1,3-decanoyl-palmitoyl- rac -glycerol) 1,3-DAG were prepared and characterized. In addition, binary phase diagrams were prepared to investigate their phase behavior and the racemate’s crystalline tendency. The major finding for this work is eutectic phase behavior was seen for blends of opposite enantiomers indicating racemic mixtures form conglomerates (mechanical mixtures of enantiopure crystals) in the solid phase. Differential scanning calorimetry melting curves of the racemic mixture display marked polymorphism, whereas, the pure enantiomer did not. This can be understood from a structural perspective since chain-end matching and hydrogen-bond optimization (via orientation of glycerol) are simultaneous for enantiopure, but are multistage for racemic DAG. Thus, there are critical differences between the crystallization behavior of enantiopure and racemic 1,3-DAG, and future physical analysis of these compounds should reflect this finding.
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 | 0.001 |
| 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".