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Record W2076726604 · doi:10.1002/aic.12689

Micro‐modeling of porous composite anodes for solid oxide fuel cells

2011· article· en· W2076726604 on OpenAlexaff
Siamak Farhad, Feridun Hamdullahpur

Bibliographic record

VenueAIChE Journal · 2011
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsAnodeMaterials sciencePorositySolid oxide fuel cellComposite numberElectrochemistryOxideMicrostructureChemical engineeringComposite materialMetallurgyChemistryElectrode

Abstract

fetched live from OpenAlex

Abstract A new anode micromodel for solid oxide fuel cells to predict the electrochemical performance of hydrocarbon‐fuelled porous composite anodes with various microstructures is developed. In this model, the random packing sphere method is used to estimate the anode microstructural properties, and the complex interdependency among the multicomponent mass transport, electron and ion transports, and electrochemical and chemical reactions is taken into account. As a case study, a porous Ni–YSZ composite anode operated with biogas fuel is simulated numerically and distributions of the current density, polarization, and mole fraction and rate of flux of the fuel components along the thickness of the anode are determined. The effect of the anode microstructural variables including the porosity, thickness, particle‐size ratio, and particle size and volume fraction of Ni particles on the anode electrochemical performance is also studied. © 2011 American Institute of Chemical Engineers AIChE J, 58: 1893–1906, 2012

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 score0.128
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.044
GPT teacher head0.287
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.

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

Citations13
Published2011
Admission routes1
Has abstractyes

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