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Record W2004070306 · doi:10.1115/icnmm2011-58172

Effect of the Hydrophilic Compact Aluminum-Foam Filled Flow Channel on Water Removal From the Cathode Catalyst Layer

2011· article· en· W2004070306 on OpenAlexaff
Brooks R. Friess, Samuel C. Yew, Mina Hoorfar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicSurface Modification and Superhydrophobicity
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsCathodeElectrolyteChemical engineeringMaterials scienceWettingWater transportLayer (electronics)Proton exchange membrane fuel cellGraphiteWater flowWaste managementComposite materialChemistryEnvironmental engineeringEnvironmental scienceElectrodeFuel cells

Abstract

fetched live from OpenAlex

The polymer electrolyte membrane (PEM) fuel cell is a zero emission power generation system that has long been considered as a replacement for conventional fossil fuel combustion systems. However, before constituting a viable market for commercial use, the fuel cell’s efficiency and reliability need to be improved significantly. It has been shown that water management has a significant effect on the power and reliability of the cell as the electrolyte membrane must be well hydrated to allow for ion transfer while excess water blocks the activation sites on the cathode side. The latter effect is known as flooding which occurs at large current densities and compromises the normal operation of the fuel cell. To enhance water management, a prodigious amount of studies have been conducted to optimize the properties and structures of different layers. One of the key results of these studies has been the design of a flow field pattern on the relatively hydrophobic surface of a graphite plate which is believed to provide a better mechanism for removing water droplets from the cathode flow channel. However, the wettability gradient between the catalyst layer (i.e., hydrophilic) and the flow channel (which is currently more hydrophobic) introduces problems as the water droplets formed at the catalyst layer will not likely detach, and hence create a film of liquid that will block the activation sites. If the flow channel is made out of a material that is more hydrophilic than the catalyst layer, water removal and transport will be enhanced as water naturally moves from low surface energy to high surface energy sites. However, recent numerical studies conducted on simulation of water transport in the channels show that removing the water film formed on the hydrophilic channels is limited due to the pressure of the gas flow in the channels. To resolve this problem, the use of compact aluminum foams in the flow channels is studied in this paper. It is shown that the hydrophilicity of the foam-filled flow channel helps the transport of the water droplets at the catalyst layer to the channel in which a liquid film is formed. This film is then removed due to the increased pressure developed in the porous media of the foam (as opposed to the regular open flow channel). The paper includes the experimental results obtained for the fuel cell performance using the new geometry with and without the gas diffusion layers (GDLs). These results will be compared to a similar flow channel that does not include the compressed aluminum porous structure. This work will result in finding the optimum geometry for achieving maximum performance in the flooding regime.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.006
Threshold uncertainty score1.000

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.037
GPT teacher head0.245
Teacher spread0.208 · 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; both teacher heads agree on what is shown here.

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
Published2011
Admission routes1
Has abstractyes

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