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Record W2377606871

Production of Carbon Nanotubes from Methane Decomposition Over a Al_2O_3 Supported Cobalt Aerogel Catalyst

2002· article· en· W2377606871 on OpenAlexaff
Pu Ling

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicAerogels and thermal insulation
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsCatalysisAerogelCalcinationCobaltReactivity (psychology)Carbon nanotube supported catalystCarbon nanotubeMaterials scienceMethaneChemical engineeringCarbon fibersDecompositionSupercritical fluidCobalt oxideInorganic chemistryCatalyst supportSpace velocityCarbon nanofiberChemistryNanotechnologyComposite materialOrganic chemistryMetallurgy
DOInot available

Abstract

fetched live from OpenAlex

An alumina supported cobalt aerogel catalyst was prepared with a sol-gel and supercritical drying method and was used in the catalytic decomposition of methane. The characterization of the physical and chemical properties of this catalyst and tests of its reactivity for catalytic decomposition of methane were investigated. The effects of calcination and reaction temperatures on the reactivity of the catalyst and the morphology of carbon nanotubes were studied. It has been observed that the catalyst oxide precursor has a CoAl 2O 4 structure. The reactivity of the catalyst increases with the amount of reduced cobalt metal in the catalyst. The growth and deactivation rate increase with the reaction temperature, and the reactivity of the catalyst decreases with the reaction temperature. An alumina supported cobalt aerogel catalyst has a high reactivity at low reaction temperature. TEM micrographs show that the carbon nanotubes obtained at 625 ℃ are hollow and curved with diameters in the range of 8~10 nm. Carbon nanotubes have even diameter and slick inner and outer wall. The diameters of the carbon nanotubes decrease with reaction temperature.

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 score0.997

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)0.0040.000

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 head0.018
GPT teacher head0.248
Teacher spread0.230 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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