Synthesis of 3D Porous Network Nanostructure of Nitrated Bacterial Cellulose Gel with Eminent Heat‐Release, Thermal Decomposition Behaviour and Mechanism
Bibliographic record
Abstract
Abstract In this study, a novel three‐dimensional (3D) porous cross‐link network structure of nitrated bacterial cellulose (NBC) nano‐gel, as an energetic gel matrix for fabrication of nanocomposite energetic materials, (nEMs) was synthesized by sol‐gel synthetic and the freeze‐drying technology. The analysis results revealed that the unique network structure with abundant of nano‐porous, which made the thermal behaviour of the NBC gel different from that of raw NBC. The thermal decomposition kinetic and mechanism of the NBC gel indicated that the exothermic peak temperature of the gel matrix decreased at low concentration, and the activation energy (Ea) of the gel0.5 (150000 J ⋅ mol−1) was much lower than that of raw NBC (223510 J ⋅ mol−1). However, the decomposition kinetic parameters of this study were not enough to illustrate the thermal properties, and which needs more effort to study them and complete. Furthermore, the initial reaction of gel decomposition was the splitting of urethane bond, and then the scission of −O−NO2 bonds happened, and the macromolecular chains’ breakage site of gel first occurred at −C−O−C− in the ring. After then, the chains of NBC break at −C−O−C− between the rings; notably, the heat‐release of gel was several times than that of raw NBC, which was liberated during the process of thermal decomposition. This promising research may provide potential application in preparing binder‐based nEMs and the basic theory of thermo‐analysis used in 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) | 0.000 | 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".