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Record W2173777650 · doi:10.1139/v11-061

Catalytic activity of Co-åkermanite and Co-pyroxene in oxidation reactions

2011· article· en· W2173777650 on OpenAlexvenueno aff
Irena Mihailova, Dimitar Mehandjiev

Bibliographic record

VenueCanadian Journal of Chemistry · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
Fundersnot available
KeywordsCobaltChemistryOctahedronPyroxeneCatalysisInorganic chemistryCrystallographySilicateCrystal structureCoordination numberIonMineralogyOrganic chemistryOlivine

Abstract

fetched live from OpenAlex

Two calcium–cobalt silicates were synthesized in which cobalt occupies different structural positions. The crystal phases belong to two main structural silicate types. In the Co-åkermanite structure (Ca 2 CoSi 2 O 7 ), cobalt cations take tetrahedral coordination toward oxygen atoms. In the Co-pyroxene structure of CaCoSi 2 O 6 , cobalt displays octahedral coordination. Ca 2 CoSi 2 O 7 was prepared by solid-phase synthesis and CaCoSi 2 O 6 was prepared by sol–gel method. The synthesis of the phases was confirmed by XRD, FTIR, and EPR data. On the basis of the XPS analysis, it can be concluded that Co 2+ cations exist in the studied silicates. Thus, it is possible to study the catalytic activity of two silicate phases containing Co 2+ cations in different coordinations: tetrahedral and octahedral. It was found that cobalt silicates with crystal structures corresponding to pyroxene and åkermanite possess catalytic activity in the reactions of complete oxidation of CO and toluene. Co-pyroxene exhibits higher catalytic activity than Co-åkermanite, but the higher cobalt content on the surface of Co-pyroxene should also be taken into account. Then, it turns out that catalytically active complexes with Со 2+ ions in tetrahedral coordination are more efficient than those with such ions in octahedral coordination when equal concentrations of cobalt were used on the surface of the catalysts.

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)0.001
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 score0.464

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 head0.024
GPT teacher head0.249
Teacher spread0.225 · 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 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

Citations11
Published2011
Admission routes1
Has abstractyes

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