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Record W2578719295 · doi:10.1149/2.0991702jes

Transient Liquid Water Distributions in Polymer Electrolyte Membrane Fuel Cell Gas Diffusion Layers Observed through In-Operando Synchrotron X-ray Radiography

2017· article· en· W2578719295 on OpenAlexaff
Rupak Banerjee, Nan Ge, Jong‐Min Lee, Michael G. George, Stéphane Chevalier, Hang Liu, Pranay Shrestha, Daniel Muirhead, Aimy Bazylak

Bibliographic record

VenueJournal of The Electrochemical Society · 2017
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Toronto
FundersU.S. Department of Energy
KeywordsElectrolyteSaturation (graph theory)Current densitySynchrotronChemistryAnalytical Chemistry (journal)TortuosityDiffusionCurrent (fluid)Materials sciencePorosityThermodynamicsChromatographyOpticsComposite materialElectrode

Abstract

fetched live from OpenAlex

In this work, in-operando synchrotron X-ray radiography was used to capture the changes in the liquid water saturation of gas diffusion layers (GDLs) during changes in operating current density. Through in-operando visualizations at high temporal and spatial resolutions, we observed that the liquid water saturation increased with increasing current density. Eventually, a threshold water content in the GDL was reached despite further increases in current density. A time lag between the change in current density and the onset of increasing GDL water content was also observed. Current density consistently reached a steady state value before the GDL water content reached steady state, and the trends in liquid water distributions in the MPL were distinct from, yet influential to the accumulation in the substrate. We present a logarithmic growth function that describes the dynamic changes in GDL water content. The formulation of the GDL liquid water content transient response to changes in operating conditions provides a new metric for designing next generation fuel cell powertrains with fast dynamic responses. Through plane water thickness profiles were also used to show that the water accumulation patterns continued to evolve for up to 15 minutes at the low current density.

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 score0.003
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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

Citations48
Published2017
Admission routes1
Has abstractyes

Explore more

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