MétaCan
Menu
Back to cohort
Record W1947470478 · doi:10.1139/cjc-2015-0266

Comparing the performance of aliphatic azido nitramines, nitrate esters, and nitro compounds: theoretical design and investigation

2015· article· en· W1947470478 on OpenAlexvenueno aff
Junqing Yang, Guixiang Wang, Xuedong Gong, Xiaoan Wei

Bibliographic record

VenueCanadian Journal of Chemistry · 2015
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
Fundersnot available
KeywordsChemistrySubstituentNitroThermal stabilityDensity functional theoryChemical stabilityContext (archaeology)Computational chemistryNitrateCombinatorial chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

To improve the low density and oxygen balance of the pure azido compounds, experimental research has been devoted to developing the modified azido compounds, such as azido nitramines, azido nitrate esters, and azido nitro compounds. Using the experimental methods to obtain a compound with suitable performance needs more resources than using theoretical tests, which makes the theoretical investigations meaningful. In this work, three azido compounds (I, II, and III) and their 27 modified derivatives were designed and studied using the density functional theory method. Results show that –NNO 2 , –NO 2 , and –ONO 2 all can improve the thermodynamic and energetic properties and the increment increases with the increasing number of substituent groups. The contribution to the thermodynamic properties is –ONO 2 > –NO 2 > –NNO 2 and that to the energetic properties is –NNO 2 > –ONO 2 > –NO 2 . The azido nitramines possess the best energetic properties and azido nitrate esters have the best thermodynamic properties. These substituents slightly decrease the thermal stability and the azido nitrate esters possess the lowest thermal stability. Systematical inspection of the substituent effect can direct experimental researchers to synthesize modified azido compounds purposefully and selectively.

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 score0.059
Threshold uncertainty score0.217

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 head0.016
GPT teacher head0.174
Teacher spread0.158 · 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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of ChemistrySame topicEnergetic Materials and CombustionFrench-language works237,207