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Record W3002211997 · doi:10.1002/ceat.201900339

Catalytic Hydrogen Production from Methane Partial Oxidation: Mechanism and Kinetic Study

2020· article· en· W3002211997 on OpenAlexfundno aff
Ahmed I. Osman

Bibliographic record

VenueChemical Engineering & Technology · 2020
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsnot available
FundersBryden Centre, Queen's University BelfastEngineering and Physical Sciences Research CouncilInterregEuropean CommissionQueen's UniversityQueen's University BelfastDepartment for the Economy
KeywordsCatalysisPartial oxidationMethaneChemistryOxideChemical engineeringHydrogen productionHydrogenCokeInorganic chemistryTransition metalNoble metalCombustionPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract The multifunctional potential of a transition and noble metal catalyst supported on either a single support or combined oxide support in the catalytic partial oxidation of methane (CPOM) is reviewed. The close interaction and interfacial area between the metal, reducible oxide, and acidic support are highlighted, which are crucial for low‐temperature CPOM. The effects of the catalyst components and their preparation methods are considered. Their impact on the catalytic performance and stability on the CPOM reaction is evaluated. The two main mechanisms of CPOM, namely, direct partial oxidation and combustion and reforming reaction, are also covered along with the most recent kinetic studies. Finally, the deactivation of the CPOM catalysts is evaluated in terms of coke and carbon deposition along with CO poisoning.

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 score0.004

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 science0.0010.000
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 head0.010
GPT teacher head0.215
Teacher spread0.205 · 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

Citations116
Published2020
Admission routes1
Has abstractyes

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