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Record W2398777727 · doi:10.1002/cctc.201600142

Ethylene Oxidation in an Oxygen‐Deficient Environment: Why Ceria is an Active Support?

2016· article· en· W2398777727 on OpenAlexafffund
Holly A. E. Dole, Elena A. Baranova

Bibliographic record

VenueChemCatChem · 2016
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOxygenCatalysisEthyleneMetalNanoparticleChemistryCarbon fibersChemical engineeringMaterials scienceInorganic chemistryNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Pt/CeO2, Ru/CeO2, Ir/CeO2 and the corresponding unsupported nanoparticles (Pt, Ru and Ir) were evaluated for their performance in the complete oxidation of ethylene in the presence and absence of oxygen. The lattice oxygen and oxygen storage capacity (OSC) of CeO2 had a significant influence on the interaction with the supported metal nanoparticles, which caused different catalytic behaviours in the absence of oxygen. Overall, Ru/CeO2 was more stable than Ir/CeO2 and Pt/CeO2, which results in transient promotional rate enhancement ratio (ρMSI; MSI=metal–support interaction) values that reach 200 in the first 25 min. These results were attributed to the corresponding interaction with CeO2 and negligible carbon deposition. A proposed relationship between ρMSI and the O2− consumed from CeO2 is discussed, which was suggested as a possible tool to estimate the extent of the MSI. In general, an increase in ρMSI corresponded to an increase in O2− consumed from ceria.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.025
GPT teacher head0.264
Teacher spread0.238 · 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

Citations19
Published2016
Admission routes2
Has abstractyes

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