Polymer Nanocomposites from Energetic Thermoplastic Elastomers and Alex®
Bibliographic record
Abstract
Abstract Polymer Nanocomposites (PNs) obtained from linear energetic copolyurethane thermoplastic elastomers (ETPEs) based on GAP and a commercially available nanometric aluminum (Alex) were characterized. Two methods were performed to prepare the PNs: in‐situ and by solvent evaporation. The thermal and mechanical properties of the pure ETPEs, of the composite ETPE/Al (micrometric) and of the nanocomposite ETPE/Alex were studied. The percentage of Alex was adjusted to obtain the optimum mechanical properties. The beneficial effects of the nanopowder on the material properties are highlighted. The introduction of nanoaluminum improves the elasticity and strength of the original ETPE and, consequently, makes it easier to use, to handle, and to process. It indicates that PNs can be considered for future applications in energetic material, such as in gun propellants, rocket propellants and insensitive melt‐cast explosive formulations.
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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".