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Record W3117987306 · doi:10.1002/slct.202004386

Safe Fabrication and Characterization of NC/CL‐20/CnMs Nanoenergetic Composite Materials via Modified Sol‐Gel

2020· article· en· W3117987306 on OpenAlexaff
Ling Chen, Yingbo Wang, You Fu, Jie Liu, Weidong He

Bibliographic record

VenueChemistrySelect · 2020
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsFabricationComposite numberExothermic reactionMaterials scienceSol-gelPropellantMatrix (chemical analysis)Chemical engineeringCentral composite designComposite materialNanotechnologyChemistryResponse surface methodologyChromatographyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract In this work, nitrocellulose/hexanitrohexaazaisowurtzitane/carbon nanomaterials (NC/CL‐20/CnMs) nanoenergetic composite materials are synthesized by combining sol‐gel and vacuum freeze‐drying technology, wherein NC is chosen as the gel matrix to load CL‐20 particles and CnMs. The results indicate that the CL‐20 and CnMs are imbedded and homogeneously dispersed in the monolithic gel of NC matrix, and the polymorph of CL‐20 maintains the optimal ϵ form during the fabrication process. The thermal results reveal that the onset temperature and exothermic temperature are visibly advanced compared with physical mixing and CL‐20. In addition, the activation energy ( E a ) of composites has also been calculated and exhibits lower E a (110 kJ mol −1 <) than that of raw materials (NC: 299.13 kJ mol −1 , CL‐20: 157.93 kJ mol −1 ). Finally, the impact and frication sensitivities have been tested and present inspirational results that sensitivity is decreased greatly owning to buffer function of the monolithic gel of NC matrix. This fabrication strategy and conclusions will provide promising application for NC/CL‐20/CnMs used in propellants.

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 score0.013
Threshold uncertainty score0.645

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 head0.007
GPT teacher head0.174
Teacher spread0.167 · 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

Citations12
Published2020
Admission routes1
Has abstractyes

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