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Record W1203319815 · doi:10.1021/acsami.5b05189

Nanostructured Materials Prepared by Surface-Assisted Reduction: New Catalysts for Methane Oxidation

2015· article· en· W1203319815 on OpenAlexafffund
A. Gomathi, S.M. Vickers, Rahman Gholami, Mina Alyani, Renee W. Y. Man, Mark J. MacLachlan, Kevin J. Smith, Michael O. Wolf

Bibliographic record

VenueACS Applied Materials & Interfaces · 2015
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of British Columbia
FundersBritish Columbia Innovation CouncilNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsMaterials scienceCalcinationNanorodFormateCeriumCatalysisMethanePalladiumNanomaterialsInorganic chemistryChemical engineeringCerium oxideSubstrate (aquarium)NanotechnologyOrganic chemistryOxideMetallurgyChemistry

Abstract

fetched live from OpenAlex

Cerium formate hollow spheres and cerium hydroxycarbonate nanorods with residual formate groups are effective for reducing palladium(II) salts onto their surfaces. Calcination of the new materials obtained by this surface-assisted reduction method gives highly active PdO/CeO2 nanostructures with Pd well dispersed on the substrate. Temperature-programmed oxidation experiments showed that these nanomaterials are good catalysts for the low-temperature oxidation of methane, with 50% conversion temperatures (T(50%)) at ∼300 °C.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
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 score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.029
GPT teacher head0.281
Teacher spread0.252 · 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.

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

Citations14
Published2015
Admission routes2
Has abstractyes

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