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Record W2109438165 · doi:10.1002/cjce.20597

Drifts and TPD analyses of ethanol on Pt catalysts over Al<sub>2</sub>O<sub>3</sub> and ZrO<sub>2</sub>—partial oxidation of ethanol

2011· article· en· W2109438165 on OpenAlexvenueno aff
Martín Schmal, Deborah Vargas César, Mariana M.V.M. Souza, Carlos E.M. Guarido

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsCatalysisPlatinumChemistryDecompositionDesorptionEthanolSelectivityPartial oxidationInorganic chemistryHeterogeneous catalysisAdsorptionDehydrationWater-gas shift reactionNuclear chemistryPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Ethanol adsorption on platinum catalysts supported on Al2O3 and ZrO2 was studied by temperature‐programmed desorption (TPD) and DRIFTS analysis. TPD of ethanol showed that the alumina support favoured the dehydration and decomposition ethanol, besides the water–gas shift reaction. DRIFTS analyses showed different intermediate species on the Pt/Al2O3 and Pt/ZrO2 catalysts. On the Pt/Al2O3 catalyst it was observed formation and decomposition of acetate species. On the Pt/ZrO2 were observed ethoxy species. Catalytic tests of the partial oxidation of ethanol showed that the H2 selectivity was higher on the Pt/Al2O3 compared to the Pt/ZrO2 catalyst. Marked difference was observed for the H2/CO ratio, suggesting preferential WGSR for Pt/Al2O3 and the reverse WGSR for the Pt/ZrO2 catalyst. These results allowed proposing different reaction routes.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.237
Teacher spread0.216 · 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

Citations31
Published2011
Admission routes1
Has abstractyes

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