The structure, binding mechanism, and properties of hollow layered and sandwiched TATB@C <sub>18</sub> and TNT@C <sub>18</sub> composites: a DFT study
Bibliographic record
Abstract
In this work, to develop new advanced energetic composites with better safety performance, composites with different proportions and sizes including TATB@C 18 , TNT@C 18 , 2TATB@C 18 , 2TNT@C 18 , TATB@2C 18 , and TNT@2C 18 were designed and constructed by an all carbon compound named cyclo[18]carbon (C 18 ) and two famous and widely used energetic compounds 1,3,5-triamino-2,4,6-trinitrobenzene (TATB) and 2,4,6-trinitrotoluene (TNT). Then, the molecular and electronic structures, binding mechanism, and properties of them were investigated theoretically. The results showed that both TATB and TNT can form stable hollow layered and sandwiched composites with C 18 through the C…O, C…N, and C…C interactions, while the binding strength of former composites is much better than that of later one. When compared to TATB and TNT, the safety performance of composites was much better. On the one hand, their impact sensitivity is lower to that of TATB or TNT slightly. On the other hand, the energy gap of TATB and TNT can be significantly reduced about 30% by C 18 . The safety performance could be flexibly adjusted by changing the proportion of TATB, TNT, or C 18 . In addition, the short recovery time and the big difference in the UV–Vis spectrum between sole TATB or TNT and composites may indicate the high potential to use C 18 as a new sensor for the explosive trace detection.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".