Novel long chain unsaturated diisocyanate from fatty acid: Synthesis, characterization, and application in bio‐based polyurethane
Bibliographic record
Abstract
Abstract A novel long chain linear unsaturated terminal diisocyanate, 1,16‐diisocyanatohexadec‐8‐ene (HDEDI) was synthesized from oleic acid via Curtius rearrangement. Its chemical structure was identified by FTIR, 1H NMR, 13C NMR, and HRMS. This diisocyanate was used as a starting material for the preparation of entirely bio‐based polyurethanes (PUs) by reacting it with canola diol and canola polyol, respectively. The physical properties and crystalline structure of the PUs prepared from this diisocyanate were compared to their counterparts prepared from similar fatty acid‐derived diisocyanate, 1,7‐heptamethylene diisocyanate (HPMDI). The HDEDI based PUs demonstrated various different properties compared to those of HPMDI based PUs. For example, HDEDI based PUs exhibited a triclinic crystal form; whereas HPMDI based PUs exhibited a hexagonal crystal lattice. In addition, canola polyol‐HDEDI PU demonstrated a higher tensile strength at break than that of canola polyol‐HPMDI, attributed to the higher degree of hydrogen bonding associated with the former sample. Nevertheless, lower Young's modulus and higher elongation in canola polyol‐HDEDI PU were obtained because of the flexibility of the long chain introduced by the HDEDI diisocyanate. © 2010 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 48: 3302–3310, 2010
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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".