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Record W2324110016 · doi:10.1149/1.2729256

Understanding Nickel Oxidation and Reduction Processes in SOFC Systems

2007· article· en· W2324110016 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

VenueECS Transactions · 2007
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRedoxAnodeOxidizing agentMaterials scienceCermetNickelDegradation (telecommunications)OxideNon-blocking I/OSolid oxide fuel cellChemical engineeringElectrodeMetallurgyInorganic chemistryChemistryCeramicCatalysisElectrical engineering

Abstract

fetched live from OpenAlex

In Solid Oxide Fuel Cells, Ni-YSZ cermets have many advantages, but degradation can be severe if the anode is exposed to an oxidizing environment. It has been found, in this study and others, that the primary cause of degradation is due to a >60% volume change from Ni to Ni oxide. It is shown here that the Ni is reduced and oxidized in a shorter time period for each redox cycle after the first full cycle. For reduction, this is likely due to the development of a larger surface area, as the cellular NiO surface structure is observed. Also, controlled oxidation of the anode leads to reduced series and reaction resistance values and the Van der Pauw technique indicates that the conductivity of the Ni-YSZ electrode improves after the first redox cycle. Thus, as long as there is enough space for the Ni to expand as it is oxidized, there are actually benefits to cell performance from redox cycling.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.648
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

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 communication0.0000.001
Open science0.0000.000
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 head0.069
GPT teacher head0.292
Teacher spread0.223 · 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