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Record W2441379794 · doi:10.1021/acscatal.6b01197

Developing a Thermal- and Coking-Resistant Cobalt–Tungsten Bimetallic Anode Catalyst for Solid Oxide Fuel Cells

2016· article· en· W2441379794 on OpenAlexafffund
Ning Yan, Jay Pandey, Yimin Zeng, Babak Shalchi Amirkhiz, Bin Hua, Norbert J. Geels, Jing‐Li Luo, Gadi Rothenberg

Bibliographic record

VenueACS Catalysis · 2016
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of AlbertaNatural Resources Canada
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaUniversiteit van Amsterdam
KeywordsBimetallic stripAnodeMaterials scienceCatalysisOxideMethaneIntermetallicChemical engineeringSolid oxide fuel cellCobaltTungstenAnnealing (glass)Steam reformingFuel cellsCobalt oxideInorganic chemistryMetallurgyHydrogen productionChemistryElectrodeMetalOrganic chemistryAlloy

Abstract

fetched live from OpenAlex

We report the development of a novel Co–W bimetallic anode catalyst for solid oxide fuel cells (SOFCs) via a facile infiltration-annealing process. Using various microscopic and spectroscopic measurements, we find that the formed intermetallic nanoparticles are highly thermally stable up to 900 °C and show good coking resistance in methane. In particular, a fuel cell fitted with Co 3 W anode shows comparable activity (relative to Co) in the electro-oxidation of hydrogen and methane at 900 °C without suffering significant degradation during a longevity test.

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 communication0.0010.001
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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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

Citations33
Published2016
Admission routes2
Has abstractyes

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Same venueACS CatalysisSame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207