Synthesis of Chlorinated and Non‐chlorinated Polyols from Model Cross‐Metathesis Modified Triacylglycerols
Bibliographic record
Abstract
Abstract Three pure triacylglycerols (TAG) containing decenoic acid (D), and stearic acid (S), were hydroxylated into chlorinated and non‐chlorinated polyols and studied in detail. D is a fatty moiety that can result from the cross metathesis of small olefins with common vegetable oils such as soybean oil. A fundamental understanding relating chemical composition and derived structure, particularly the number and position of the hydroxyl groups, to physical properties was established allowing us to add some perspective to the growing body of knowledge on industrially relevant polyol and polyurethane systems produced with metathesis‐modified TAG (MTAG). The hydroxyl value, crystallization and melting behaviors, thermal degradation behavior of the polyols were directly related to their peculiar shortened and primary functionality inherited from the parent MTAG. The effect of regiochemistry on the physical properties of the polyols was investigated with the chromatography fractions of the trichlorinated polyol of propane‐1,2,3‐triyl tris(dec‐9‐enoate), giving an unhindered insight into the role of short and terminal functionality of MTAG polyols that will help select the optimal isomer composition for designer polyurethane materials.
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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) | 0.001 | 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".