Two-dimensional titanium carbide (Ti<sub>3</sub>C<sub>2</sub>) MXene towards enhancing thermal catalysis decomposition of dihydroxylammonium 5,5′-bistetrazole-1,1′-diolate (TKX-50)
Bibliographic record
Abstract
In this study, we demonstrated that two-dimensional (2D) MXene materials (Ti3C2) were creatively introduced into the thermal catalysis fields of high energy density salts dihydroxylammonium 5,5′-bistetrazole-1,1′-diolate (TKX-50) and Ti3C2 MXene materials play a significant catalytic role in the thermal decomposition of TKX-50. Scanning electron microscopy, X-ray diffraction, and transmission electron microscopy were used to characterize the morphology and structure of the Ti3C2 MXene nanosheets. Differential scanning calorimetry was used to evaluate the thermal decomposition properties of pure TKX-50 with and without 2D Ti3C2 added. The results showed that with adding 5 wt% MXene, the peak temperature of TKX-50 was reduced from 250.5 to 233.3 °C, which is a reduction of 17.2 °C. The reaction heat release increased from 2197 to 2907 J g−1, which is an increase of 710 J g−1. The Ea was decreased by 44.8 kJ mol−1, from 220.0 to 175.2 kJ mol−1. Moreover, a synergistic catalytic mechanism for the thermal decomposition of TKX-50 was proposed.
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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".