MétaCan
Menu
Back to cohort
Record W1907476834 · doi:10.1149/1.1479156

Stabilization of Platinum Anode Catalyst in a H[sub 2]S-O[sub 2] Solid Oxide Fuel Cell with an Intermediate TiO[sub 2] Layer

2002· article· en· W1907476834 on OpenAlexafffund
Pan He, M. Liu, Jing‐Li Luo, Alan R. Sanger, K. T. Chuang

Bibliographic record

VenueJournal of The Electrochemical Society · 2002
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Alberta
KeywordsAnodePlatinumElectrolyteMaterials scienceYttria-stabilized zirconiaCatalysisElectrochemistrySolid oxide fuel cellInorganic chemistryChemical engineeringOxideCathodeCubic zirconiaChemistryElectrodeComposite materialMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

The performance of supported platinum as an anode catalyst in a hydrogen sulfide solid oxide fuel cell with yttria-stabilized zirconia (YSZ) as the electrolyte has been examined in the temperature range of 700-900°C. The highest current density achieved at 800°C was 100 mA/cm2 and the highest power density was 15.4 mW/cm2, when operated with 5% feed. Increasing the concentration of in the anode feed did not improve the performance of the cell, due to corruption of the platinum anode; the reversible formation and decomposition of PtS on the platinum-YSZ interface led to instability of the electrochemical interface of the Pt catalyst with the YSZ electrolyte. The membrane structure and performance were both stabilized by interposing a thin layer of between the Pt anode and YSZ electrolyte. The stabilized open-circuit voltage value depended on flow rates of the anode and cathode feeding gases. This behavior is attributed to the crossover of reactants, which change the partial pressures of product and © 2002 The Electrochemical Society. All rights reserved.

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 score0.002
Threshold uncertainty score0.634

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 integrity0.0000.001
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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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

Citations31
Published2002
Admission routes2
Has abstractyes

Explore more

Same venueJournal of The Electrochemical SocietySame topicAdvancements in Solid Oxide Fuel CellsFrench-language works237,207