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Record W2970186535 · doi:10.1002/fuce.201800113

Performance and Properties of Suspension Plasma Sprayed Metal‐Supported Cu‐Co‐Ni‐SDC SOFC Anodes in Methane

2019· article· en· W2970186535 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFuel Cells · 2019
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsCanada Research ChairsUniversity of TorontoUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnodeMaterials scienceSolid oxide fuel cellMetalOxideDiffusionChemical engineeringCoatingMethaneFabricationMetallurgyComposite materialElectrodeChemistry

Abstract

fetched live from OpenAlex

Abstract In this study, metal‐supported solid oxide fuel cell (SOFC) anodes containing Cu and samaria doped ceria (SDC) with additions of Ni and Co were evaluated in CH 4 . It was found that metal support oxidation and Fe diffusion from the metal support to the anode were the main factors affecting the cell behavior observed. Thus, strategies to prevent diffusion of Fe into the anode were also evaluated. It was found that the best performing method to prevent diffusion of Fe and Cr into the anode in this study consisted of a combination of all three evaluated strategies (i.e., pre‐oxidation of metal support prior to cell fabrication, application of a protective LaCrO 3 coating to the metal supports prior to anode fabrication, and addition of an SDC interlayer between the metal support and anode coating). It was found that the most effective stand‐alone method to diminish the diffusion of Fe into the anode was the addition of a SDC interlayer between the anode and the metal support.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.005
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.246
Teacher spread0.226 · 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