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Record W2331579535 · doi:10.1149/1.2921528

Characterization of the Catalyst Layer in a PEMFC During Subzero Operation

2008· article· en· W2331579535 on OpenAlexfundno aff
Stephen Lee, Joy Roberts, Jing Li, Siyu Ye

Bibliographic record

VenueECS Transactions · 2008
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsnot available
FundersUniversity of British Columbia
KeywordsIsothermal processStack (abstract data type)Characterization (materials science)Materials scienceLayer (electronics)Proton exchange membrane fuel cellMembraneCatalysisChemical engineeringIn situElectrodeNanotechnologyChemistryComputer scienceEngineeringOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

In-situ isothermal constant voltage (ICV) experiments and stack freeze start-ups at -25{degree sign}C, in combination with ex-situ image analysis (Cryo-FESEM) has been used to investigate the behaviour of product water at subzero temperatures. Use of these tools enables more small scale, rapid material screening to design membrane electrode assemblies (MEAs) with improved subzero operation capability. Cryo-FESEM images at different stages of sustained subzero operation suggests that any ice present prior to operation melts and migrates away from the membrane towards the GDL where it is frozen along with newly produced product water. More and more water is frozen until reactants can no longer reach the catalyst sites.

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)0.000
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 score0.085
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.171
Teacher spread0.163 · 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

Citations1
Published2008
Admission routes1
Has abstractyes

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