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BORON NANOPARTICLE-RICH FUELS FOR GAS GENERATORS AND PROPELLANTS

2010· article· en· W1992452216 on OpenAlexaff
R. Lima, Charles Dubois, Oliver Mader, Robert Stowe, Sophie Ringuette

Bibliographic record

VenueInternational Journal of Energetic Materials and Chemical Propulsion · 2010
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsDefence Research and Development CanadaPolytechnique Montréal
Fundersnot available
KeywordsMaterials scienceBoronPropellantNanoparticleCombustionPolymerChemical engineeringParticle (ecology)PolyurethaneNanotechnologyComposite materialOrganic chemistryChemistry

Abstract

fetched live from OpenAlex

This study reports on the production and characterization of energetic polymer-capped boron for solid fuel applications. It is known that the addition of metal and metal-like particles to solid fuels and propellants can improve the performance of both rocket and air-breathing propulsion systems. The use of boron is very attractive for these applications due to its high heat of combustion on both a gravimetric (58 kJ/g) and volumetric (136 kJ/cm3) basis. However, the exploitation of the high theoretical energy of boron has been limited by a few undesirable properties of this metal. Among them, one notes the existence of a resilient oxide layer on the particle surface affecting the ignition and combustion of boron particles. The capping of boron nanoparticles with a polymer can provide a solution to the aforementioned problem. The use of an energetic polymer for that purpose can bring additional heat close to the surface of the nanoparticles and facilitate their ignition. In the present work, boron nanoparticles were produced by synthesis of surface-functionalized boron. The route was adapted to obtain additional hydroxyl-functional groups on the particles. These hydroxyl sites were used to graft a diisocyanate, and then produce an energetic polymer matrix based on polyurethane chemistry by addition of glycidyl azide polymer, resulting in boron nanoparticles coated by energetic polymers. This can lead to significantly enhanced boron particle combustion.

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 score0.008
Threshold uncertainty score0.357

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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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

Citations15
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Energetic Materials and Chemical PropulsionSame topicEnergetic Materials and CombustionFrench-language works237,207