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Record W2069292154 · doi:10.1080/15435075.2010.515185

Effects of Hardware Design and Operation Conditions on PEM Fuel Cell Water Flooding

2010· article· en· W2069292154 on OpenAlexafffund
Jianlu Zhang, Hui Li, Zheng Shi

Bibliographic record

VenueInternational Journal of Green Energy · 2010
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsBC Innovation Council
FundersNational Research Council Canada
KeywordsProton exchange membrane fuel cellFlooding (psychology)Relative humidityEnvironmental scienceWater flowMembraneEnvironmental engineeringHumidityCurrent (fluid)Materials scienceWaste managementFuel cellsChemical engineeringChemistryEngineeringElectrical engineeringMeteorology

Abstract

fetched live from OpenAlex

In this paper, membrane electrode assemblies were constructed using catalyst-coated membranes to investigate proton-exchange membrane fuel cell water flooding. Two major fuel cell hardware variations, namely flowfield design and Teflon loading of the gas diffusion layer (GDL), were tested to explore their effects on water flooding. A flowfield with triple serpentine flow channels showed heavier water flooding than that with single serpentine flow channels. Increasing the Teflon loading in the GDL reduced water flooding effectively. Several fuel cell operating conditions, including air stoichiometry, current density, relative humidity (RH), backpressure, and temperature, were also tested to identify their effects on water flooding. It was observed that the water flooding severity increased with decreasing air stoichiometry, as well as with increasing temperature, RH, backpressure, and current density. Among these operation conditions, air stoichiometry (or air flow rate) and RH played more important roles in reducing water flooding.

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 score0.080
Threshold uncertainty score0.224

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 head0.004
GPT teacher head0.190
Teacher spread0.187 · 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

Citations39
Published2010
Admission routes2
Has abstractyes

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