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Record W2102451756 · doi:10.1139/cjc-2014-0396

Improving an insensitive low-energy compound, 1,3,4,6,7,9-hexaazacycl[3.3.3]azine, to be an insensitive high explosive by way of two-step structural modifications

2014· article· en· W2102451756 on OpenAlexvenueno aff
Qiong Wu, Guolin Xiong, Zhichao Liu, Dong Xiang, Chunhong Yang, Weihua Zhu, Heming Xiao

Bibliographic record

VenueCanadian Journal of Chemistry · 2014
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
FundersPriority Academic Program Development of Jiangsu Higher Education InstitutionsGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsAzineExplosive materialChemistryDetonationLow energyCrystallographyCombinatorial chemistryOrganic chemistryAtomic physicsPhysics

Abstract

fetched live from OpenAlex

We improved an insensitive low-energy compound, 1,3,4,6,7,9-hexaazacycl[3.3.3]azine (HAA), to be an insensitive high explosive by a useful approach of two-step structural modifications. First, the three carbon atoms in HAA are substituted by three new nitrogen atoms symmetrically to form a new energetic compound, 1,2,3,4,5,6,7,8,9-nonaazacycl[3.3.3]azine (NAA). Then, introducing three N-oxides into NAA symmetrically generates another new energetic compound, 1,2,3,4,5,6,7,8,9-nonaazacycl[3.3.3]azine-2,5,8-trioxides (NAATO). The energetic properties and sensitivity of NAATO were studied by using density functional theory. The results indicate that NAATO has higher detonation performance than RDX and comparative sensitivity to TNT, indicating that it has outstanding overall performance and may be considered as a potential candidate of insensitive high explosives. Thus, the insensitive low-energy compound HAA was successfully improved to be an insensitive high explosive by the two-step structural modifications.

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 score0.006
Threshold uncertainty score0.918

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 head0.006
GPT teacher head0.186
Teacher spread0.180 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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