Study of Moisture-Curable Hybrid NIPUs Based on Glycerol with Various Diamines: Emergent Advantages of PDMS Diamines
Bibliographic record
Abstract
A sol/gel curing method is used in this work to synthesize hybrid partially bio-based polyhydroxyurethanes (PHUs) from dicarbonates derived from glycerol and various diamines. The method consists of end-capping the PHU prepolymers with moisture-sensitive groups, so sealants and adhesives can be produced from partially sustainable hybrid PHUs (HPHUs), similar to their preparation from end-capped conventional polyurethanes. Diglycerol dicarbonate (DGC) is synthesized and polymerized with different diamines of various chain lengths, and the resulting structural and thermal properties of the PHUs are qualitatively and quantitively characterized. This characterization led to two potential candidates: PHU 4, made of DGC and a poly(propylene glycol) diamine, and PHU 10, prepared from DGC and a poly(dimethylsiloxane) diamine. These polymers, with respective relative number-average molecular weights of 3200 and 7400 g/mol, are end-capped and left to cure under ambient lab conditions (22 °C and 40-50% humidity), and the curing processes are monitored rheologically. Notably, moisture curing does not require any catalyst. The chemical stability of the resulting hybrid PHUs (HPHUs) 4 and 10 in pure water is investigated to check the viability of applying them under outdoor conditions. Only HPHU 10 is found to be resistant to water and shows hydrophobicity with a contact angle of 109°. Tensile tests are conducted on HPHU 10 samples cured under lab conditions for a week and others cured for another week while being immersed in water. The mechanical properties, tensile strength and elongation at break, improve with the samples cured in water, indicating the high-water repellency of HPHU 10.
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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".