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Record W3047893492 · doi:10.5383/swes.7.01.006

Fe Supported Alumina Catalyst for Methane Decomposition: Effect of Co Coupling

2015· article· en· W3047893492 on OpenAlex
Anis H. Fakeeha, Ahmed A. Ibrahim, Ahmed S. Al‐Fatesh, Wasim Ullah Khan, Yahya Mohammed, Ahmed E. Abasaeed, Mostafa I. Soliman, Raja Alotaibi

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Sustainable Water and Environmental Systems · 2015
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsnot available
FundersKing Abdulaziz City for Science and Technology
KeywordsCatalysisMethaneDecompositionHydrogenHydrogen productionOxidative coupling of methaneMaterials scienceChemical engineeringChemistryInorganic chemistryOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

In recent years hydrogen production received enormous attention, since it is an environmentally friendly, energy source. The aim of this research was to examine the hydrogen production with the help of methane’s catalytic decomposition. 30% Fe coupled with different % of Co over alumina support, were examined by catalytic decomposition of methane for the production of hydrogen. The catalysts were prepared by impregnation method. The catalytic activity results revealed that the catalysts, coupled 15% Co gave the highest conversion of 72.5% as depicted by the three hour time on stream profile. The fresh and spent catalysts were characterized using different techniques such as BET, H2-TPR, and XRD.

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.

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)0.001
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 score0.005
Threshold uncertainty score0.423

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.255
Teacher spread0.247 · 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