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Record W2042193699 · doi:10.1149/05802.0159ecst

The Effect of Particle Size on the Performance of LSFC Perovskite Anode of Proton Conducting Solid Oxide Fuel Cell (PC-SOFC)

2013· article· en· W2042193699 on OpenAlexafffund
Yifei Sun, Ning Yan, Guangya Wang, Jing‐Li Luo, Karl T. Chuang

Bibliographic record

VenueECS Transactions · 2013
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCalcinationAnodeSolid oxide fuel cellMaterials scienceParticle sizeOxidePerovskite (structure)Chemical engineeringElectrochemistryParticle (ecology)Inorganic chemistryCatalysisChemistryMetallurgyElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

A promising and stable perovskite structure anode material La 0.3 Sr 0.7 Fe 0.7 Cr 0.3 O 3-x (LSFC) prepared by a glycine nitrate process was applied as the anode catalyst of a proton conducting solid oxide fuel cell (PC-SOFC). The particle size of the anode material could be controlled by varying the calcination temperatures. The influence of particle sizes on electrochemical performances had been studied. It was shown that the higher calcination temperature resulted in larger LSFC particles, which decreased the PC-SOFC performance significantly.

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 score0.007
Threshold uncertainty score0.733

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 science0.0000.000
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 head0.015
GPT teacher head0.255
Teacher spread0.239 · 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

Citations4
Published2013
Admission routes2
Has abstractyes

Explore more

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