Potential Use of CL‐20 in TNT/ETPE‐Based Melt Cast Formulations
Bibliographic record
Abstract
Abstract An attempt was made to introduce CL‐20 in a TNT/energetic thermoplastic elastomer (ETPE)‐based melt cast formulation, to obtain an insensitive composition with reduced adverse environmental properties. A loading limit of 42% w/w of CL‐20 in melted TNT was observed, while it should have been around 70%. This paper describes the investigation that was undertaken to understand the observed phenomena. It was demonstrated that CL‐20 undergoes structural alterations in melted TNT. The relative solubility of CL‐20, RDX and HMX in melted TNT was determined and the α‐, β‐, γ‐ and ε‐CL‐20 were prepared and characterized using Raman spectroscopy and DTA. CL‐20 was mixed in melted TNT, as much as 4.2 g of CL‐20 dissolved in 100 g of TNT. This allowed a transformation from ε to β‐CL‐20 and a modification of CL‐20 particle size and distribution. The later modification induced a raise in CL‐20 specific surface and was responsible for the loading limit, while the transformation to β‐CL‐20 caused an increase in sensitivity and a decrease in density. This indicates that the use of CL‐20 in TNT melt cast is not promising. Our study also showed that CL‐20 is sensitive to morphological transformations, which should be taken into consideration in future processing using this compound.
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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) | 0.002 | 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".