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Record W2053248744 · doi:10.5539/mas.v3n2p35

The Investigation of Active Sites on Nickel Oxide Based Catalysts towards the In-situ Reactions of Methanation and Desulfurization

2009· article· en· W2053248744 on OpenAlexvenueno aff
Wan Azelee Wan Abu Bakar, Mohd. Yusuf Othman, Rusmidah Ali, Ching Kuan Yong, Susilawati Toemen

Bibliographic record

VenueModern Applied Science · 2009
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
FundersMinistério da Ciência, Tecnologia e InovaçãoKementerian Sains, Teknologi dan Inovasi
KeywordsCatalysisMethanationNickelFlue-gas desulfurizationX-ray photoelectron spectroscopyIncipient wetness impregnationOxideMaterials scienceAdsorptionInorganic chemistryDesorptionSulfurNuclear chemistryChemistryChemical engineeringMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

Supported nickel oxide based catalysts of Fe/ Co/ Ni (10: 30: 60)-Al2O3 and Pr/ Co/ Ni (5: 35: 60)-Al2O3 that were prepared by wetness impregnation method showed potential catalysts for the in-situ reactions of H2S desulfurization and CO2 methanation from ambient temperature up to 300 oC. X-ray Photoelectron Spectroscopy revealed Ni2O3 and Fe3O4 as the surface active components on the Fe/ Co/ Ni (10: 30: 60)-Al2O3 catalyst, while Ni2O3 and Co3O4 on the Pr/ Co/ Ni (5: 35: 60)-Al2O3 catalyst. Energy Dispersive X-ray analysis indicated the presence of 2.7 % and 0.9 % of sulfur on the spent Fe/ Co/ Ni (10: 30: 60)-Al2O3 and Pr/ Co/ Ni (5: 35: 60)-Al2O3 catalysts, respectively. N2 adsorption-desorption analysis showed reduction of 5.5 % on the surface area of the spent Fe/ Co/ Ni (10: 30: 60)-Al2O3 catalyst. However, the surface area of the spent Pr/ Co/ Ni (5: 35: 60)-Al2O3 catalyst increased by 8.6 %.

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 score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.269
Teacher spread0.243 · 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

Citations28
Published2009
Admission routes1
Has abstractyes

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