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Record W2805101268 · doi:10.17628/ecb.2018.7.106-114

POTENTIAL ENVIRONMENTAL IMPACT OF NANOENERGETICS

2018· article· en· W2805101268 on OpenAlexafffund
Nancy N. Perreault

Bibliographic record

VenueEuropean Chemical Bulletin · 2018
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsNational Research Council Canada
FundersMinistère de la Défense Nationale
KeywordsExplosive materialNanomaterialsNanotechnologyEnergetic materialMaterials scienceCarbon nanotubeFullereneEnvironmental chemistryEnvironmental scienceChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Nanoenergetics has the potential to become the next generation of explosives and propellants. Nano-explosives often show better performances in terms of energy release, ignition and mechanical properties compared to their bulk counterparts. In addition to monomolecular explosives such as nano-TNT and nano-RDX, diverse energetic nanocomposites have been developed, including the nanometer-sized versions of conventional thermites (nanothermites) and those using carbon-based nanomaterials (e.g., fullerenes and carbon nanotubes). While the unique characteristics of nanomaterials allow groundbreaking applications, they also result in distinct environmental fate, transport and toxicity. The high surface to volume ratio and reactivity of nanomaterials make them highly dynamic in environmental systems. Once released in the environment, nanoenergetic chemicals will undergo transportation and transformation processes including dissolution, aggregation, adsorption, photolysis and biotransformation, which will also affect their persistence and bioavailability. This review was conducted to better understand the potential environmental fate and ecological impact of the use of nanoenergetics.

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 categoriesInsufficient payload (model declined to judge)
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 score0.998

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)0.0030.001

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 head0.003
GPT teacher head0.171
Teacher spread0.168 · 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.

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

Citations1
Published2018
Admission routes2
Has abstractyes

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