Thermal and Mechanical Properties of Triazole Cross‐Linked Glycidyl Azide (GAP) and Azido Polycarbonate Networks
Bibliographic record
Abstract
Abstract Triazole cross‐linked energetic polymer networks obtained from the reaction of dialkyne curing agents with glycidyl azide polymers (GAP) or poly(2,2‐[bisazidomethyl]propane‐1,3‐diyl carbonate) (poly[BAMPC]) were studied, and their thermal and mechanical properties are reported. The dialkynes studied include bis(propargyl)ether (BPE), bis(propargyl)malonate (BPM), and 4,4’‐diacyanohepta‐1,6‐diyne (DCHD), three compounds previously described as curing agents for glycidyl azide pre‐polymers. The cured polymer networks display a wide range of properties dependent on the nature of the azido pre‐polymer, the nature of the dialkyne, the alkyne/azide molar ratio, and the molecular weight of the pre‐polymer used. Results confirm that the three dialkynes are effective curing agents able to form rigid networks out of either pre‐polymer and that the lighter molecular weight BPE and DCHD both improve mechanical properties of cured networks with less dilution of the system's energetic content. Triazole cross‐linked poly(BAMPC) networks were studied for the first time, and promising physical and mechanical properties are reported.
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 | 0.000 |
| 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".