MétaCan
Menu
Back to cohort
Record W2009193186 · doi:10.1088/0022-3727/37/15/011

Carbon nanotubes from the dissociation of C<sub>2</sub>Cl<sub>4</sub>using a dc thermal plasma torch

2004· article· en· W2009193186 on OpenAlexafffund
D. Harbec, Laina Guo, R Gauvin, N El Mallah

Bibliographic record

VenueJournal of Physics D Applied Physics · 2004
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarbon nanotubeDissociation (chemistry)PlasmaThermalChemistryPlasma torchAnalytical Chemistry (journal)Nonthermal plasmaCarbon fibersTorchChemical engineeringMaterials scienceNanotechnologyPhysical chemistryEnvironmental chemistryPhysicsMetallurgyThermodynamicsNuclear physicsComposite number

Abstract

fetched live from OpenAlex

Carbon nanotubes (CNTs) are produced using a 100 kW dc non-transferred plasma torch and C2Cl4 as the carbon precursor. Catalytic metallic nanoparticles are generated in situ using the tungsten metal vapours emitted by the electrode erosion process. Large quantities of multi-walled carbon nanotubes (MWNTs) and spherical (onion-like) carbon structures are observed under FE-SEM and TEM. Preliminary results are given here on the effect of the type and pressure of the gas in the reactor on the zone of CNT nucleation. A large amount of CNTs, over 50 µm in length, is observed to grow within the torch nozzle at 0.26 atm pressure in helium and argon. Increasing the pressure to 0.66 atm in both gases has the effect of pushing the CNT production downstream in the gas phase within the main reactor.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.013
GPT teacher head0.228
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations26
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Physics D Applied PhysicsSame topicCarbon Nanotubes in CompositesFrench-language works237,207