MétaCan
Menu
Back to cohort
Record W2729318748 · doi:10.1149/ma2017-02/35/1565

Tracking Degradation Induced Structural and Compositional Changes of a Polymer Electrolyte Fuel Cell Cathode Catalyst Layer Following Voltage Cycling Using Micro-Xct

2017· article· en· W2729318748 on OpenAlexaffabout
Robin White, Sebastian H. Eberhardt, Marina Najm, Francesco P. Orfino, Monica Dutta, Erik Kjeang

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldMaterials Science
TopicElectron and X-Ray Spectroscopy Techniques
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMaterials scienceElectrolyteDegradation (telecommunications)CathodeChemical engineeringCatalysisLayer (electronics)Carbon fibersComposite materialElectrodeChemistryComposite numberOrganic chemistry

Abstract

fetched live from OpenAlex

Degradation of cathode catalyst layers during typical automotive operation is a concern for long-term durability and performance of polymer electrolyte fuel cells (PEFCs). Although many degradation pathways exist, carbon corrosion following significant voltage fluctuations should be considered a primary degradation mechanism due to the role carbonaceous material plays in catalyst layer composition and structure. Following carbon support corrosion, catalytic activity is lost due to removal, isolation, or agglomeration of catalyst particles. Eventual collapse of the weakened carbon support structure can lead to changes in porosity and pore size distribution, thus blocking transport pathways for gas flow and water removal. Furthermore, changes in surface roughness and composition by addition of surface oxidation groups can increase hydrophilicity, increasing the possibility of flooding in the catalyst layer [ 1]. A detailed understanding of the structural and compositional changes that occur following degradation of the catalyst layer is therefore required. To date, imaging of PEFC component degradation, in particular the cathode catalyst layer, has primarily been limited to ex situ techniques and associated qualitative morphological observations [ 2, 3]. Recent developments in lab-based X-ray computed tomography (XCT) systems have allowed for nondestructive in situ imaging of PEFCs [ 4] accomplished by using a unique device fixture design and XCT operation to obtain same location tracking with high quality three-dimensional tomographies over different stages of cathode catalyst layer (CCL) degradation [ 5]. In this work, this technique is expanded to visualize and measure quantitative morphological and compositional changes that occur with degradation of the cathode catalyst layer during voltage cycling, see Figure 1. This analysis is combined with simultaneous tracking of the liquid water distribution in the gas diffusion layer and CCL by specialized operandovisualization, not previously performed for lab-based XCT. The attenuation of X-rays is related to the elemental composition as well as the density of the material being imaged as defined by the Beer-Lambert law. By exploiting this property, novel insight into the local compositional changes of the cathode catalyst layer are investigated and uniquely correlated to the water distribution changes in an operating fuel cell, which has not been previously possible. The acquired compositional and morphological changes are further supplemented with electrochemical diagnostics measurements such as fuel cell polarization curves, electrochemical active surface area (ECSA) and double layer capacitance. This comprehensive study highlights the effect of CCL degradation on overall fuel cell performance. Significant losses in the mass transport regime of the polarization curve are correlated to possible flooding of the catalyst layer and reduced oxygen transport through observation of density increase and reduced thickness. Local material composition changes such as carbon loss, ionomer distribution and platinum loading are also calculated and discussed. 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. Fairweather, J. D. et al., Fuel Cells. J. Electrochem. Soc. 160 (9), F980-F993 (2013). 2. Deevanhxay, P., Sasabe, T., Minami, K., Tsushima, S. & Hirai, S., Electrochim. Acta 135, 68-76 (2014). 3. Hwang, G. S. et al., Electrochim. Acta 95, 29-37 (2013). 4. White, R. T., Najm, M., Dutta, M., Orfino, F. P. & Kjeang, E. J. Electrochem. Soc. 163 (10), F1206-F1208 (2016). 5. White, R. T. et al., J. Power Sources 350, 94-102 (2017). 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.031
GPT teacher head0.306
Teacher spread0.275 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueECS Meeting AbstractsSame topicElectron and X-Ray Spectroscopy TechniquesFrench-language works237,207