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Record W2610749312 · doi:10.1149/07801.1293ecst

Degradation of Metal-Supported Cells with Ni-YSZ or Ni-Ni<sub>3</sub>Sn-YSZ Anodes Operated with Methane-Based Fuels

2017· article· en· W2610749312 on OpenAlexafffund
Jeffrey Harris, Elisa Lay-Grindler, Craig Metcalfe, Olivera Kesler

Bibliographic record

VenueECS Transactions · 2017
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAnodeMaterials scienceElectrolyteCathodeYttria-stabilized zirconiaTinDegradation (telecommunications)Chemical engineeringMetallurgyElectrodeChemistryCubic zirconiaElectrical engineering

Abstract

fetched live from OpenAlex

Ni-Ni3Sn-YSZ and Ni-YSZ anodes were incorporated into metal-supported SOFCs that consisted of a porous metal support (Sandvik Sanergy), samaria-doped ceria (SDC) barrier layer, anode as previously described, YSZ electrolyte, and La0.6Sr0.4Co0.2Fe0.8O3-δ-SDC cathode. Cells were tested at 750°C with air as the oxidant and fuel consisting of 65% CH4, 32% H2, and 3% H2O. The cells were held at a current density of 0.15 A·cm-2 for 500 hours. The cell without tin in the anode began to degrade after approximately 200 hours and catastrophically failed at approximately 425 hours. After testing, we observed that the anode had disintegrated, and as a result, the electrolyte and cathode were completely detached from the metal support. On the other hand, the cell with an anode containing tin did not catastrophically fail, and the cell remained intact after 500 hours of operation. Over 500 hours, the cell potential degraded from 0.841 V to 0.743 V, and scanning electron micrographs showed that the anode had delaminated from the electrolyte in some areas. Nonetheless, the cell with the Ni-Ni3Sn-YSZ anode degraded significantly less than the cell containing a Ni-YSZ anode, suggesting that the addition of Ni3Sn to an anode could be a useful strategy for improving durability of SOFC anodes using hydrocarbon fuels.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.174
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.270
Teacher spread0.244 · 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.

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

Citations2
Published2017
Admission routes2
Has abstractyes

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