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Record W2512328198 · doi:10.1149/ma2016-02/38/2519

In Situ Visualization of Cathode Catalyst Layer Degradation in Fuel Cells Using X-Ray Computed Tomography

2016· article· en· W2512328198 on OpenAlexaffabout
Robin White, Alex Wu, Monica Dutta, Erik Kjeang

Bibliographic record

VenueECS Meeting Abstracts · 2016
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCathodeDielectric spectroscopyMaterials scienceDegradation (telecommunications)CorrosionScanning electron microscopeChemical engineeringCyclic voltammetryElectrolytePlatinumDurabilityElectrochemistryCatalysisNanotechnologyComposite materialElectrodeChemistryElectrical engineeringOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

Polymer electrolyte fuel cells (PEFCs) have been growing in popularity as an alternative energy source for a multitude of applications, including the automotive industry. The use of fuel cells in these applications requires long-term durability with minimal degradation to be cost competitive against conventional technology sources. Current targets for automotive applications are >5,000 hours, under realistic operating conditions. One primary degradation pathway associated with these operating conditions is that of cathode catalyst support corrosion, which occurs due to the oxidation of carbon support for platinum nanoparticles, leaving the platinum unsupported and inactive. The pathway for this degradation mechanism is at elevated cathode potentials greater than 1.2 V RHE , where significant carbon corrosion, in the presence of water, occurs at rates high enough to cause significant structural degradation effects. These elevated potentials can occur during fuel starvation or gas switching during start-up and shutdown procedures [1]. A significant amount of effort has been devoted toward research regarding cathode degradation rates and mitigation, primarily using methods such as electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and scanning electron microscopy (SEM). These methods provide information on a global, two-dimensional perspective. That is, SEM typically provides information on catalyst layer thinning by 2-D cross-sectional images, and EIS and CV provide overall electrochemical changes affected by changes in surface area from carbon corrosion. The usefulness of the proposed X-ray computed tomography (XCT) technique is in its non-invasive nature, excellent spatial resolution, and three-dimensional imaging abilities. These advantages allow for observations to be made on a local and global level providing further insight into the cathode catalyst layer degradation process. Typically research regarding XCT is performed at a synchrotron beamline which is significantly limiting in that it is expensive, impractical and available in only short time intervals. This means that investigating in-situ degradation effects is extremely difficult. 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 an investigation toward understanding cathode catalyst layer degradation mechanisms through in-situ visualization by commercial XCT using a fully functional dual-channel, small-scale, fuel cell fixture [2]. This small-scale fixture allows imaging of the membrane electrode assembly (MEA) at multiple stages of its lifecycle during an accelerated stress test, targeting the cathode catalyst layer, in this case causing carbon corrosion. Differences under land and channel are investigated as well as water distribution, which is shown to have a significant effect on the degradation rate using a sample containing catalyst layer cracks. Image processing techniques used to obtain quantitative results are discussed which include histogram deconvolution and thresholding. Figure 1 shows the thresholding procedure results, indicating differences found under land and channel. Continued research using this tool hopes to further our understanding of the interconnectivity within a fuel cell. 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] A. Young, V. Colbow, D. Harvey, E. Rogers, and S. Wessel. J. Electrochem. Soc . 160 (4) F381-F388 (2013) [2] R. White, M. El Hannach, O. Luo, F. Orfino, M. Dutta and E. Kjeang. ECS abstract 58394, presented at 228 th ECS meeting, Phoenix, AZ. Oct. 11-16, 2015 Figure 1: a) 3D visualization of a full MEA highlighting local thresholding ability b) 2D segmented area of cathode catalyst at BOL and EOL c) plot showing area fraction of solid to crack change during accelerated stress test d) cross-section of regions used in calculations for the plot above. The image shows a single slice from the End of Life (EOL) sample 3D reconstruction 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 score0.359
Threshold uncertainty score0.447

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 head0.236
Teacher spread0.221 · 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
Published2016
Admission routes2
Has abstractyes

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