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Record W2623378581 · doi:10.14447/jnmes.v13i3.167

Tungsten effect over co-hydrotalcite catalysts to produce hydrogen from bio-ethanol

2010· article· en· W2623378581 on OpenAlexvenueno aff
J.I. Contreras París, M.A. Ortiz, Gustavo A. Fuentes, Rosario Luna, J. Salmones, B. Zeifert, L. Nuño, Araceli Espinoza-Vázquez

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2010
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsnot available
Fundersnot available
KeywordsHydrotalciteCatalysisPhysisorptionHydrogen productionTungstenHydrogenChemistryInorganic chemistryMesoporous materialNuclear chemistryMaterials scienceChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

A great stabilization effect of tungsten over the Co-hydrotalcite catalysts to produce H2 from ethanol in steam reforming was found. The catalysts were characterized by N2 physisorption (BET area), X-ray diffraction, Infrared ,Raman and UV-vis spectroscopies. Catalytic evaluations were performed in a fixed bed reactor using a water/ethanol mol ratio of 4, at 450°C, and the W concentration stud- ied was from 0.5 to 3 wt%. As W concentration increases, the intensity of crystalline reflections of the Co-hydrotalcite catalysts decreases. There were found porous with the shape of parallel layers with a monomodal mesoporous distribution. Superficial chemical groups as: -OH, H2O, Al-OH, Mg-OH, W-O-W and CO32- were found by infrared spectroscopy. Catalyst with low amounts of W (1%) showed both, the highest H2 production and the best catalytic stability. The smallest pore volume of this catalyst could be related with long residence times of ethanol in the pores. Tungsten promoted the conversion for the Co-hydrotalcite catalysts. The reaction products were: H2, CO2, CH3CHO, CH4 and C2H4 and the catalysts did not produce CO.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.009
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.008
GPT teacher head0.263
Teacher spread0.255 · 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

Citations5
Published2010
Admission routes1
Has abstractyes

Explore more

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