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Record W2266306088 · doi:10.1149/ma2015-02/37/1541

3D Printed Flow Channel Fixture for Visualization of Water Condensation in PEFC By X-Ray Computed Tomography

2015· article· en· W2266306088 on OpenAlexaffabout
Robin White, Mohamed El Hannach, Oliver Luo, Monica Dutta, Erik Kjeang

Bibliographic record

VenueECS Meeting Abstracts · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNuclear Physics and Applications
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsNeutron imagingMaterials scienceProcess engineeringTurbinePower densityNeutronNuclear engineeringComputer sciencePower (physics)Mechanical engineering

Abstract

fetched live from OpenAlex

Polymer electrolyte fuel cells (PEFC) have been shown to have significant potential for automotive applications as an alternate clean energy technology with zero emissions at the point of use. The many advantages include quick start-up time, low operating temperature, low weight, high efficiency and relatively simple design [1]. Despite these advantages however a primary reason for the delay of this technology from meeting commercial application standards is cost. Significant cost reductions are possible by increasing the power density, which is currently limited by liquid water related mass transport effects at high current densities. Higher power density cells are also an advantage for automotive applications due to a better form factor for vehicles. Due to the components that make up a membrane electrode assembly (MEA) and fuel cell, many current in situ visualization techniques for water visualization utilize neutron imaging, since it has the advantage of being sensitive to hydrogen containing compounds such as water and other components of the PEFC, while being insensitive to metals that make up compression plates and current collectors. Neutron imaging is, however, limited by its spatial resolution and has extremely high cost with limited availability since the technique requires a nuclear reactor [2]-[4]. The usefulness of X-ray computed tomography (XCT) is in its non-invasive nature, excellent spatial resolution and better sensitivity to membrane electrode assembly (MEA) component materials. X-rays have the ability to pass through materials with the attenuation scaling with atomic number and density. This causes the sensitivity of X-rays to be extremely low for hydrogen, however all other components such as carbon, oxygen, nitrogen and metals, such as platinum, provide sufficient contrast to observe all fuel cell components and liquid water. Much of the initial work involving XCT of fuel cells was done using synchrotron radiation as the X-ray source. This is primarily due to the intensity of the beam, and is still used by researchers with access to synchrotron sources. This research however is extremely expensive and impractical for a large majority of research groups without access to a synchrotron source. With advances in commercial X-ray sources, optics and detectors for laboratory use, many researchers are now being able to take advantage of the power of XCT scans with much lower cost and increased availability. In this work we present a novel approach toward the beginnings of unraveling liquid water distribution in PEFCs by the use of rapid prototyping 3D printed materials to create a small scale flow channel fixture for 3D XCT visualization of a full MEA. Unlike previous research, water condensation, formation, and transport within a cell can be observed by drawing current from the cell to allow for in situ water production before imaging at an equilibrium state. Comparison of dry un-operated MEAs to humidified (zero current drawn) and wet (operated) MEAs is used to more clearly define water content and distribution with results shown in figure 1. Other processing techniques such as image subtraction are performed to better enhance the changes during operation. Preliminary results show significant water content after operation with high saturation seen on the cathode side on the surface of the GDL. Water content also varies across the width of the sample with trapped liquid water beneath the channel landing on both anode and cathode sides. Other changes such as membrane swelling and resultant movement in catalyst layer are also observed. Continued investigation using this tool shows great promise toward further understanding changes occurring on all facets of this dynamic system during fuel cell operation. Acknowledgements Funding for this research was provided by the Natural Sciences and Engineering Research Council of Canada, Canada Foundation for Innovation, British Columbia Knowledge Development Fund, and Ballard Power Systems through an Automotive Partnership Canada grant. References [1] M. M. Mench, Fuel Cell Engines. John Wiley & Sons, 2008. [2] A. Turhan, K. Heller, J. S. Brenizer, and M. M. Mench, Journal of Power Sources, vol. 160, no. 2, pp. 1195–1203, Oct. 2006. [3] R. Satija, D. L. Jacobson, M. Arif, and S. A. Werner, Journal of Power Sources, vol. 129, no. 2, pp. 238–245, Apr. 2004. [4] R. J. Bellows, M. Y. Lin, M. Arif, A. K. Thompson and D. Jacobson J. Electrochem. Soc. vol.146, no. 3, pp.1099-1103. 1999 Figure 1

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 score0.179
Threshold uncertainty score0.377

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 head0.015
GPT teacher head0.254
Teacher spread0.239 · 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".

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Citations0
Published2015
Admission routes2
Has abstractyes

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