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Record W2315603924 · doi:10.1149/05701.1025ecst

Improved Electrolyte Performance in Plasma Sprayed SOFCs by Electrode Modification

2013· article· en· W2315603924 on OpenAlexafffund
Michael Marr, Craig Metcalfe, Eric Sheung‐Chi Fan, Olivera Kesler

Bibliographic record

VenueECS Transactions · 2013
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Toronto
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaResearch and Innovation Foundation
KeywordsElectrolyteAnodeCathodeMaterials scienceElectrodePorosityOpen-circuit voltageChemical engineeringComposite materialAnalytical Chemistry (journal)VoltageChemistryElectrical engineeringChromatography

Abstract

fetched live from OpenAlex

Electrolytes were deposited by atmospheric suspension plasma spraying (SPS) in metal-supported SOFCs having both anode- and cathode-down configurations. The electrodes on the metal supports were intentionally made thin (< 30 μm) and smooth (average roughness < 2.5 μm) to reduce the formation of segmentation cracks and concentrated porosity in the electrolytes. In the anode-down cells, the electrolytes had minimal concentrated porosity and no segmentation cracks were observed. Open circuit voltages (OCVs) were above 1.05 V at 750 °C in cells with 21 μm thick electrolytes. The electrolytes in cathode-down cells had higher leak rates than those in the anode-down cells, and segmentation cracks were observed in some cathode-down cell electrolytes. The cathode-down cells having the most gas-tight electrolytes were electrochemically tested. OCVs were initially above 1.04 V, though performance declined significantly within 2-4 hours. In contrast, the OCVs of the anode-down cells were approximately constant after 12 hours of testing.

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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.170
Teacher spread0.166 · 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

Citations4
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueECS Transactions→Same topicFuel Cells and Related Materials→French-language works237,207→