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Record W4322494645 · doi:10.1021/acs.cgd.2c01448

pH-Dependent Formation of Two Dihydrazinyltetrazine–Azobistetrazolate Salts with Different Thermal Stabilities and Energetic Performance

2023· article· en· W4322494645 on OpenAlexafffund
Darren Herweyer, Alexandros A. Kitos, Paul Richardson, Hussein Canoe, Jeffrey S. Ovens, Isabelle Laroche, Benoit Jolicoeur, Muralee Murugesu, Jaclyn L. Brusso

Bibliographic record

VenueCrystal Growth & Design · 2023
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsGeneral Dynamics (Canada)University of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaMitacsUniversity of Ottawa
KeywordsThermogravimetric analysisDifferential scanning calorimetryChemistrySalt (chemistry)Hydrogen bondThermal decompositionTetrazineCrystallographyDecompositionCrystal structureSingle crystalPowder diffractionThermal analysisPhysical chemistryMoleculeThermalOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

Two new energetic salts were prepared through the combination of 3,6-dihydrazinyl-1,2,4,5-tetrazine dichloride ([H 2 DHT]Cl 2 ) and disodium 5,5′-azobis(tetrazolate) pentahydrate (Na 2 AZT·5H 2 O) in different pH conditions. Under acidic conditions, the 1:1 salt [H 2 DHT][AZT]·2H 2 O ( 2 ·2H 2 O) was isolated, while neutral pH gave access to the formation of the 2:1 salt ([HDHT] 2 [AZT]·4H 2 O; 3 ·4H 2 O). Both compounds were characterized by IR and NMR spectroscopy, thermal analysis (thermogravimetric analysis and differential scanning calorimetry), as well as single crystal and powder X-ray diffraction. Based on experimental data, compound 2 ·2H 2 O was found to be more thermally stable, with a decomposition temperature of T dec = 107 °C, compared to compound 3 ·4H 2 O ( T dec = 99 °C). Non-covalent interactions (hydrogen bonds and π–π interactions) were evaluated to better understand the structure–property relationships, revealing the effect of crystal packing on the overall energetic properties.

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 score0.018
Threshold uncertainty score0.641

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 head0.011
GPT teacher head0.186
Teacher spread0.175 · 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

Citations6
Published2023
Admission routes2
Has abstractyes

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