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Record W3090807579 · doi:10.1139/cjc-2020-0210

Computational studies of energetics, electronic structure, and vibrational spectra of PETN nanoparticles

2020· article· en· W3090807579 on OpenAlexvenueno aff
Qiannan Ma, Weihua Zhu

Bibliographic record

VenueCanadian Journal of Chemistry · 2020
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
Fundersnot available
KeywordsPentaerythritol tetranitrateChemistryExplosive materialChemical physicsMoleculeNanoparticleEnergeticsDecompositionBand gapMolecular dynamicsDensity functional theoryComputational chemistryNanotechnologyMaterials scienceOrganic chemistryThermodynamicsOptoelectronics

Abstract

fetched live from OpenAlex

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 NO 2 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.185
Teacher spread0.178 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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