Fabrication of nitrocellulose‐based nanoenergetic composites, study on its structure, thermal decomposition kinetics, mechanism, and sensitivity
Bibliographic record
Abstract
Abstract In order to investigate the thermal decomposition kinetics and mechanism of nitrocellulose (NC) based nitramine explosives nanocomposite energetic materials, this work prepares NC/RDX (cyclotrimethylenetrinitramine), NC/HMX (cyclotetramethylenetetranitramine), and NC/CL‐20 (hexanitrohexaazaisowurtzitane) composites by a combined sol‐gel and the freeze‐drying technology. The structure is systematically investigated and the results reveal that the explosive particles are dispersed, filled, or embedded homogenously in the gel matrix of NC, thereby restricting the crystal growth of RDX, HMX, CL‐20 particles to coarse and achieving submicron/nanometer. The thermal analysis of composites exhibits much lower peak temperature compared with raw explosive crystal, furthermore, the activation energy ( E a ) of composites is also lower than that of both NC and explosives. Hence, the unique structure of NC gel matrix embedded explosives inside demonstrated different mechanism of decomposition. Concretely, the rupture of the H‐NCO = O bond in the cross‐linked structure is detected firstly, subsequently, the macromolecular chains’ scission site of gel firstly occurs at ‐C‐O‐C‐ in the ring, and then the scission of ‐NO 2 (from NC or explosive crystals) bonds happened. Hence, this study may provide promising fabrication strategy and basic theory for the application of NC‐based nanocomposite energetics in high‐energy propellants and explosives.
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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".