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Record W2083663414 · doi:10.2495/sdp-v8-n2-186-196

Production of methane from carbon monoxide and carbon dioxide in a plasma-catalytic combined reactor system

2013· article· en· W2083663414 on OpenAlexvenueno aff
Young Sun Mok, Eunjin Jwa, H.W. Lee

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2013
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsnot available
FundersMinistry of Education, Science and TechnologyNational Research Foundation of KoreaNational Research Foundation
KeywordsCatalysisMethaneCarbon monoxideDissociation (chemistry)Dielectric barrier dischargeNonthermal plasmaNickelInorganic chemistrySyngasCarbon dioxideCarbon fibersMaterials scienceMethanationMethanizerOxygenPlasmaChemical engineeringChemistryElectrochemical reduction of carbon dioxideDielectricOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

Plasma-catalytic hydrogenation of CO and CO 2 for producing methane was investigated with a catalyst-packed dielectric barrier discharge reactor. The characteristics of methane production from CO/H 2 or CO 2 /H 2 gas mixture were examined with bare alumina, TiO 2 /alumina, Ni/alumina, and Ni-TiO 2 /alumina under plasma and non-plasma conditions. The results obtained with bare alumina and TiO 2 /alumina suggest that either plasmainduced gas-phase reactions or photocatalytic reactions hardly contribute to the conversion of CO and CO 2 . The nonthermal plasma was found to have a promotive effect on the conversion of CO and CO 2 only when nickel-loaded catalysts such as Ni/alumina and Ni-TiO 2 /alumina were used, implying that the nonthermal plasma serves to promote the dissociation of carbon-oxygen bonds of CO and CO 2 adsorbed on the active sites of the catalysts, known as the slowest step of the reaction.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.340

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 head0.012
GPT teacher head0.239
Teacher spread0.227 · 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 designObservational
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

Citations5
Published2013
Admission routes1
Has abstractyes

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