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Record W2904157362 · doi:10.1139/cjc-2018-0466

Theoretical study on polyglycerine polynitrates for potential high-energy plasticizers of propellants

2018· article· en· W2904157362 on OpenAlexvenueno aff
Guixiang Wang, Yimin Xu, Wenjing Zhang, Chuang Xue, Xuedong Gong

Bibliographic record

VenueCanadian Journal of Chemistry · 2018
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsBond-dissociation energyChemistryPropellantPlasticizerDetonationBond energyThermodynamicsEnergetic materialStandard enthalpy of formationPhysical chemistryComputational chemistryDissociation (chemistry)Organic chemistryMoleculeExplosive materialPhysics

Abstract

fetched live from OpenAlex

Polyglycerine polynitrates such as nitroglycerine can be used as energetic plasticizers of propellants. In this study, 29 derivatives of nitroglycerine are investigated at the B3LYP/6-31G* level of the density functional theory. The corrected theoretical densities ([Formula: see text]) are predicted and are found to be very close to the experimental values. Detonation properties are calculated using the modified Kamlet–Jacobs equations and the specific impulse (I s ) is evaluated according to the maximum exothermic principle. A new parameter K, which is the product of I s and [Formula: see text], is proposed to evaluate the overall energetic characteristics of compounds. Thermal stability is discussed by calculating the bond dissociation energies or bond dissociation energy barriers. The O–NO 2 bond has the smallest bond dissociation energy and is the trigger bond for each of the studied compounds. The influence of the –ONO 2 and –CH 2 –O–CH 2 –CH(ONO 2 )– groups, which is useful for design of new high energy plasticizers, is also discussed. Comprehensively considering the energetic properties and the stability, DGPN, DGHN, TriGHeptaN, TriGON, TriGNN, TetraGNN, TetraGDeN, TetraGUN, and TetraGDoN are possibly better energetic plasticizers of solid propellants than nitroglycerine.

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 score0.017
Threshold uncertainty score0.627

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 head0.004
GPT teacher head0.180
Teacher spread0.176 · 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
Published2018
Admission routes1
Has abstractyes

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