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Record W2789010198 · doi:10.1139/cjc-2017-0381

High-nitrogen nitrotetrazole substituted tetrazole 3-<i>N</i>-oxides as potential high energy density compounds

2018· article· en· W2789010198 on OpenAlexvenueno aff
Qiong Wu, Qidi Li, Kai Li, Hang Li, Bo Kou, Zusheng Hang, Weihua Zhu

Bibliographic record

VenueCanadian Journal of Chemistry · 2018
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
Fundersnot available
KeywordsTetrazoleChemistryDetonationDensity functional theoryDetonation velocityNitrogenStandard enthalpy of formationOxygen balanceComputational chemistryPhysical chemistryOxygenInorganic chemistryOrganic chemistryExplosive material

Abstract

fetched live from OpenAlex

In this work, two series of novel high-nitrogen tetrazole 3-N-oxides substituted by different nitrotetrazoles were designed, and their structure and properties were investigated by using the density functional theory (DFT) method. The results shown that though there are only one to two energetic substituents in the structure, because of the high nitrogen content, ideal oxygen balance, and the big conjugated structure, all eight designed compounds not only have high heat of formation (655.4–845.6 kJ/mol), high density (1.83–1.93 g/cm 3 ), and high detonation performance (detonation velocity: 9.06–9.50 km/s; detonation pressure: 36.7–41.8 GPa), but also possess reduced impact sensitivity (23–98 cm). Fully analyzing the energy and sensitivity, A1 and A4 have higher energy and lower sensitivity than one famous high energy compound 1,3,5,7-tetranitro-1,3,5,7-tetrazocane (HMX), and A3, B1, and B4 have comparable overall performance with HMX, showing that these five designed compounds may be considered as the potential high energy density compounds. In addition, the introduction of one extra nitro group into the tetrazole 3-N-oxide could not improve the combination property generally.

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 score0.004
Threshold uncertainty score0.895

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)0.0010.000

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 head0.003
GPT teacher head0.157
Teacher spread0.154 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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