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Record W4249944013 · doi:10.1149/ma2019-02/32/1410

Insights into the Evolution of Chemical Degradation in Fuel Cell Membranes Using 4D in Situ Visualization

2019· article· en· W4249944013 on OpenAlexaffabout
Dilip Ramani, Yadvinder Singh, Robin White, Tylynn Haddow, Francesco P. Orfino, Monica Dutta, Erik Kjeang

Bibliographic record

VenueECS Meeting Abstracts · 2019
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsMembraneChemical imagingMaterials scienceDegradation (telecommunications)IonomerMembrane electrode assemblyChemical engineeringPolymerCharacterization (materials science)Composite materialChemistryNanotechnologyElectrodeElectrolyteCopolymerComputer science

Abstract

fetched live from OpenAlex

Ionomer membrane degradation during fuel cell operation is conjointly produced by three different modes, namely, thermal, mechanical, and chemical. Amongst these, chemical degradation is generally considered a major contributor to lifetime limitations.[1] Chemical degradation of the ionomer membrane is caused by the formation of radical species, such as hydroxyl (OH•) and hydroperoxyl (HOO•) groups, which causes polymer chain scission and unzipping leading to membrane thinning and eventual rupture and shorting events. Furthermore, the chemical degradation deteriorates the mechanical properties of the membrane which dramatically accelerates its overall degradation rate. Scanning electron microscopy (SEM) based studies have been conventionally used to conduct two-dimensional characterization of degradation-induced structural features in fuel cell membranes; however, SEM imaging is inherently destructive and thus prohibits any tracking of structural changes over time. Laboratory-based X-ray computed tomography (XCT) is as an alternative imaging technique, which has not only enabled three-dimensional (3D) membrane failure analysis revealing novel insights on membrane failure [2,3], but has also facilitated studies on damage growth characterization, [4] and more recently on evolutionary aspects of mechanical membrane degradation through identical-location imaging. [5] In the present work, an XCT-based 4D in situ imaging method, featuring three dimensions in space and one dimension in degradation time, is applied to investigate the evolution of pure chemical membrane degradation through the use of a custom designed fixture housing a fully operational small-scale fuel cell. [6] Membrane electrode assemblies (MEAs) with three distinct membrane types, namely, i) non-reinforced, ii) mechanically reinforced, and iii) chemically and mechanically mitigated membranes, are separately examined and compared. The MEAs were subjected to open circuit voltage (OCV) hold under high temperature (75°C) and low humidity (30% RH) with 0.3 slpm H2 and 0.5 slpm air supplied to anode and cathode, respectively. Various in situ electrochemical diagnostics were periodically performed to monitor MEA and membrane health. XCT-based 3D datasets were obtained at various stages of degradation to facilitate identical location tracking and analysis of membrane morphology as a function of degradation time and enable the characterization of damage evolution in the three membrane types. Membrane thinning and other damage features within all three membranes are comprehensively examined from various perspectives by studying planar and cross-sectional views extracted from the 3D XCT datasets. Preliminary observations show that electrode-shorting under land regions was the key failure mode for membranes without chemical mitigation, i.e., non-reinforced and mechanically reinforced membranes (Fig. 1). In contrast, the chemically mitigated membrane did not fail up to 850 h of operation, highlighting the scavenging effect against the radicals. No membrane pinhole or crack development was observed in any of the three membranes, which is consistent with previous 3D post mortem results under pure chemical degradation.[3] The present 4D in situ imaging approach further revealed locally amplified membrane thinning preceding the eventual formation of shorts due to absence of membrane material and associated loss of electrode separation. The observed phenomenon further suggests that mechanical stresses, even in the absence of wet/dry cycling, may influence the local shorting events. Overall, the new findings from this work demonstrate the distinct advantage of XCT technology towards improving the fundamental understanding of membrane degradation by capturing critical failure modes and mechanisms at their different developmental stages. Acknowledgements This research was supported 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. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. W. L. Gore & Associates, Inc. is acknowledged for additional support. References [1] W. Chen et al. J. Power Sources 51 (2006) 2391–2399. [2] Y. Singh et al. J. Power Sources 345 (2017) 1–11 [3] Y. Singh et al. J. Electrochem. Soc. 164 (2017) F1331-41 [4] D Ramani et al. J. Electrochem. Soc. 165 (2018) F3200-08 [5] Y. Singh et al. J. Power Sources 412 (2019) 224–37 [6] R.T. White et al. J. Power Sources 350 (2017) 94-102 Figure 1: Cross-sectional identical location MEA images obtained by XCT at beginning of life (BOL) and end of test (EOT) for separate MEAs with: a) non-reinforced; b) mechanically reinforced; and c) chemically and mechanically mitigated membranes subjected to pure chemical degradation. The encircled areas indicate the shorting sites at EOT. 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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.212
Teacher spread0.205 · 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".

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Citations0
Published2019
Admission routes2
Has abstractyes

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