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Record W2002061416 · doi:10.2202/1542-6580.1074

Combating Deactivation in Methane Non-Oxidative Dehydrocyclization via Hydrogen Feed Pulsing

2003· article· en· W2002061416 on OpenAlexfundno aff
Maria C. Iliuta, Ion Iliuta, Bernard P. A. Grandjean, Faı̈çal Larachi

Bibliographic record

VenueInternational Journal of Chemical Reactor Engineering · 2003
Typearticle
Languageen
FieldChemical Engineering
TopicCatalysts for Methane Reforming
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCatalysisCokeBenzeneMethaneHydrogenHydrogen productionMaterials scienceChemical engineeringIncipient wetness impregnationChemistryInorganic chemistryOrganic chemistryMetallurgySelectivity

Abstract

fetched live from OpenAlex

The non-oxidative dehydrocyclization of methane was carried out over Ru–Mo/HZSM-5 catalyst in a fixed-bed catalytic reactor between 873 and 973 K. The catalyst, prepared by incipient wetness co-impregnation, was highly selective towards benzene production. The formation and deposition of low-H/C carbonaceous species was found to be more important at high temperatures and high methane space velocities. Intermittent hydrogenation of the catalyst by periodically switching from CH4 stream to pure hydrogen in the feedstream contributed significantly to the regeneration of active sites through hydrogenation of the carbonaceous species. Coke removal from the catalyst during H2 exposure was confirmed through temperature programmed oxidation and mass spectrometry analyses of spent catalyst. Alternating sequences of dehydrocyclization and hydrogenation under moderate and high feed flow rates resulted in improving catalyst stability due to efficient reduction of coke formation. These results might suggest an option for maintaining relatively high catalyst activity towards benzene production for prolonged reaction times.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.246
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

Citations0
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Chemical Reactor EngineeringSame topicCatalysts for Methane ReformingFrench-language works237,207