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Record W2293316272

Effect of the Microstructure of Porous Composite Electrodes on the Electric Power Density of Solid Oxide Fuel Cells

2011· book-chapter· en· W2293316272 on OpenAlexaff
Siamak Farhad, Feridun Hamdullahpur

Bibliographic record

VenueASME eBooks · 2011
Typebook-chapter
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMaterials scienceSolid oxide fuel cellPower densityElectrodeMicrostructurePorosityComposite numberComposite materialYttria-stabilized zirconiaOxideElectrochemistryMetallurgyPower (physics)AnodeThermodynamicsChemistryCeramic
DOInot available

Abstract

fetched live from OpenAlex

The electric power density generated in co-flow planar solid oxide fuel cells (SOFCs) with porous composite electrodes is predicted using the cell combined micro- macro-model; and the effect of the microstructural variables of the electrodes on the cell power generation is studied. In the combined micro- macro-model, the electrochemical performance of the porous composite electrodes is determined from the micro-model and the distributions of the temperature in solid structure of the cell and the temperature and species partial pressures of the bulk fuel and air streams are determined from the cell macro-model. As a case study, the effect of the microstructural variables of the porous composite electrodes of the Ni-YSZ/YSZ/LSM-YSZ cell operated at the given voltage, fuel utilization ratio, and excess air, on the average power density of the cell is investigated through computer simulation. The results reveal that there is an optimum value for each microstructural variables of the electrodes at which the cell power density is maximized.© 2011 ASME

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)0.000
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 score0.003

Distilled classifier scores by category (both heads)

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.223
Teacher spread0.215 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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Same venueASME eBooksSame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207