Thermal kinetics, thermodynamics, decomposition mechanism, and thermal safety performance of typical ammonium perchlorate-based molecular perovskite energetic materials
Bibliographic record
Abstract
In this work, we report the thermal kinetics, thermodynamics, and decomposition mechanism of AP-based molecular perovskite energetic materials and estimate their thermal safety performance. Typical AP-based molecular perovskite energetic materials, (H 2 dabco)[NH 4 (ClO 4 ) 3 ] (DAP-4), (H 2 pz)[NH 4 (ClO 4 ) 3 ](PAP-4), (H 2 mpz)[NH 4 (ClO 4 ) 3 ](PAP-M4), and (H 2 hpz)[NH 4 (ClO 4 ) 3 ] (PAP-H4), were synthesized and characterized. These were studied using differential scanning calorimetry (DSC). The results show that all of the obtained AP-based molecular perovskite energetic materials have higher thermal decomposition temperatures, and the peak temperatures are more than 360 °C. All follow random nucleation and growth models. Other thermodynamic parameters, such as the reaction enthalpy (ΔH), entropy change (ΔS), and Gibbs free energy (ΔG), show that they are generally thermodynamically stable. Moreover, their adiabatic induced temperatures were obtained; T D 24 of DAP-4, PAP-4, PAP-M4, and PAP-H4 were 246.6, 201.2, 194.5, and 217.5 °C, respectively. This study offers an important and in-depth understanding of the thermal decomposition characteristics of AP-based molecular perovskite energetic materials and their potential applications.
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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 | 0.001 |
| 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".