Computational studies of energetics, electronic structure, and vibrational spectra of PETN nanoparticles
Bibliographic record
Abstract
The density functional tight binding method was used to explore the energetics, electronic structure, and vibrational spectra of pentaerythritol tetranitrate (PETN) nanoparticles (NPs). The surface energy of the PETN NP is anisotropic and its extra energy decreases with the increase of size. The energy bands of the NPs are significantly expanded and the band gaps are narrowed, thus reducing the stability due to nanometer size effect. The surface of the NP is mainly covered by the NO2 group. The high-energy surface may play a role in triggering chemical decomposition. The vibration frequencies of the PETN NPs present a wider distribution than those of the gas and solid phase PETN, which will increase the probability of energy transfer to the molecules in the system and promote the decomposition of PETN. Our results provide a basic understanding from a molecular perspective to the energy properties of nano 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".