Design of new aliphatic azido nitro compounds as plasticizer: an initial exploration on AFCTEE (1-azido-formic acid 1,1,1-trinitro-ethyl ester)
Bibliographic record
Abstract
To explore new high-energy azido nitro compounds as plasticizers for propellants, AFCTEE (1-azido-formic acid 1,1,1-trinitro-ethyl ester) was designed and studied using density functional theory. The predicted density of AFCTEE, 1.90 gcm−3, is comparable to that of HMX (1,3,5,7-tetranitro-1,3,5,7-tetraazacyclooctane) and much higher than that of general organic azido compounds. AFCTEE possesses higher energetic properties and chemical stability than the promising azido nitro plasticizer DAMNP (1,3-diazido-2-methyl-2-nitropropane) and the conventional plasticizer NG (nitroglycerine), and it has a moderate thermal stability. The pyrolysis of AFCTEE starts from the rupture of C–NO2 and then the breakage of N–N2 via Curtius rearrangement. This work is the initial exploration for AFCTEE, aiming at the energetics, spectra (IR, NMR, and UV), stability, and decomposition mechanism. Compared with DAMNP, the advantages of superior energetic properties and chemical stability suggest AFCTEE is a promising energetic azido nitro compound and is worth further investigation.
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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".