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Record W2092077006 · doi:10.1149/1.3116252

Metal–Oxide Scale Interfacial Imperfections and Performance of Stainless Steels Utilized as Interconnects in Solid Oxide Fuel Cells

2009· article· en· W2092077006 on OpenAlexafffund
Nima Shaigan, Douglas G. Ivey, Weixing Chen

Bibliographic record

VenueJournal of The Electrochemical Society · 2009
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOxideMaterials scienceSpallationAuger electron spectroscopyMetallurgyX-ray photoelectron spectroscopyMetalConductivityScanning electron microscopeImpurityComposite materialChemical engineeringChemistry

Abstract

fetched live from OpenAlex

Ferritic stainless steels currently used as the interconnect materials in solid oxide fuel cells do not exhibit adequate electronic conductivity over expected periods of service. In addition to the relatively poor conductivity of the oxide scales, the metal–oxide scale interfacial defects contribute to significant conductivity losses. In this work, the metal–oxide scale interfacial defects are studied for two grades of stainless steels, AISI-SAE 430 and ZMG232. Scanning electron microscopy, as well as surface science analysis techniques including Auger electron spectroscopy, X-ray photoelectron spectroscopy, and secondary-ion mass spectroscopy, was used to study the metal–oxide scale interface for AISI-SAE 430 and for ZMG232 coupons. Oxide scale spallation occurred during rapid cooling of oxidized AISI-SAE 430 steels. Large, micrometer-sized cavities appeared beneath the spalled scales on AISI-SAE 430. The metal substrate is not in contact with the scale in these locations. Moreover, for this steel, nonmetallic and metallic impurities, such as Si, S, Cl, N, F, Pb, V, and Al, segregate at the metal–oxide scale interface and result in reduced metal-to-scale adhesion and contact area. However, no marked impurity segregation and spallation occur for ZMG232, which contains Zr and La as reactive elements that prevent impurity segregation.

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 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 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 score0.005
Threshold uncertainty score0.641

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.007
GPT teacher head0.259
Teacher spread0.252 · 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 teacher head, 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

Citations25
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207