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Record W2962809303 · doi:10.1002/cjce.23605

Beneficial effect of adding γ‐AlOOH to the γ‐Al<sub>2</sub>O<sub>3</sub> washcoat of a PdO catalyst for methane oxidation

2019· article· en· W2962809303 on OpenAlexafffundvenue
Hamad AlMohamadi, Kevin J. Smith

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2019
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBoehmiteMonolithCatalysisCalcinationMethaneThermal stabilityChemical engineeringCordieriteCeramicChemistryMaterials scienceMetallurgyAluminiumOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The beneficial effect of adding γ‐AlOOH to the γ‐Al 2 O 3 washcoat of a ceramic cordierite (2MgO · 2Al 2 O 3 · 5SiO 2 ) monolith, used to support a PdO catalyst, is reported for methane oxidation in the presence of water at low temperature (&lt;500°C). The mini‐monolith (400 cells per square inch (CPI), 1 cm diameter × 2.54 cm length; ~52 cells) was washcoated using a suspension of γ‐Al 2 O 3 plus boehmite (γ‐AlOOH), followed by calcination and then deposition of Pd by wet impregnation. An optimum solid content of 25 wt% in the washcoat suspension was used to obtain a ~25 wt% washcoat on the monolith. The presence of γ‐AlOOH enhanced the thermal and mechanical stability of the washcoat, provided that the γ‐AlOOH content was &lt;8 wt%. Temperature‐programmed methane oxidation (TPO) showed that the addition of γ‐AlOOH to the γ‐Al 2 O 3 washcoat decreased the catalyst activity. However, when H 2 O (2 vol% and 5 vol%) was present in the feed gas, the γ‐AlOOH improved the catalyst activity and stability. A γ‐AlOOH content of ~5 wt% in the washcoat was determined to provide the highest catalyst activity and stability for CH 4 oxidation in the presence of water.

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 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 score0.011
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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

Citations9
Published2019
Admission routes3
Has abstractyes

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