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Record W4235675118 · doi:10.1149/ma2018-01/30/1769

Structure, Properties, and Degradation of Ultrathin Ionomer Films in Fuel Cell Catalytic Layers

2018· article· en· W4235675118 on OpenAlexaff
Renate Hiesgen, Tobias Morawietz, Michael Handl, C. Oldani, Kunal Karan, K. Andreas Friedrich

Bibliographic record

VenueECS Meeting Abstracts · 2018
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIonomerMaterials scienceNafionElectrodeAgglomerateNanostructureElectrolytePolymerChemical engineeringComposite materialNanotechnologyElectrochemistryCopolymerChemistry

Abstract

fetched live from OpenAlex

The performance of polymer electrolyte fuel cells and electrolysers depends on the nanostructure of its components. Mainly the nanostructured electrodes determine cell performance and degradation. In working fuel cell electrodes, the ionomer films that encapsulate the Pt/C agglomerates have a thickness of 4-20 nm and fall within the range of ultrathin films [1]. In recent years, an oxygen transport resistance has been identified as a major hurdle in the development of low-loaded MEAs and the ionomer layer has been postulated to be the reason for additional loses [2]. The quantitative investigation of the nanostructure of fuel cell electrodes, especially the analysis of the correct dimensions of the ionomer component has proven to be exceptionally difficult. Using electron beam-based techniques that need vacuum the ionomer is drying and significantly shrinking in addition to a low contrast between ionomer and carbon components. Also cryogenic TEM analysis may alter the sample by use of alcoholic solvents that have an input on structure, despite of beam damage. Atomic force microscopy (AFM) has the advantage to work in humid environment and at elevated temperatures, close to operational conditions [3]. Using material-sensitive tapping mode, the high contrast between the ionomer- and the Pt/C phase in adhesion force mapping allows studying the distribution and thickness of the ionomer films that cover the Pt/C agglomerates (Figure 1a) [3,4]. In this contribution, the analysis of cross-sections of Nafion- and Aquivion–based fuel cell electrodes by material-sensitive AFM will be presented. Analysis of pristine electrodes delivers the distribution of the ionomer films, small ionomer clusters, and larger agglomerates. A distribution of ionomer films ranging from roughly 4 to 20 nm was retrieved (Figure 1b). After operation, significant thinning of the ionomer films depending on location within the membrane-electrode-assembly and preparation was found. Differences of the swelling behavior of the ionomer films prior and after operation were used as a measure for ionomer degradation. Part of the thinning was assigned to ionomer redistribution during operation. A dependence of macroscopic cell degradation on initial electrode ionomer film thickness was observed. For further determination of the properties of such ultrathin films model layers of Nafion®, and Aquivion® PFSA were examined. Conductive AFM allowed investigations of through- and in-plane conductivity in dependence of the film thickness. Significant differences in conductivity for films below 10 nm thickness were detected (Figure 1c). References [1] S. Holdcroft, Fuel Cell Catalyst Layers: A Polymer Science Perspective, Chem. Mater. 26, 381–393 (2014) [2] A. Kongkanand, M. F. Mathias, The Priority and Challenge of High-Power Performance of Low-Platinum Proton-Exchange Membrane Fuel Cells, J. Phys. Chem. Lett., 7, 1127−1137 (2016) [3] R. Hiesgen, T. Morawietz, M. Handl, M. Corasaniti, K.A. Friedrich, Atomic Force Microscopy on Cross Sections of Fuel Cell Membranes, Electrodes, and Membrane Electrode Assemblies, 162, Electrochimica Acta, 86–99 (2015) [4] T. Morawietz, M. Handl, C. Oldani, K.A. Friedrich, R. Hiesgen, Quantitative in Situ Analysis of Ionomer Structure in Fuel Cell Catalytic Layers, ACS Appl. Mater. Interfaces, 8, 27044–27054 (2016) Figure 1: (a) AFM adhesion force mapping of electrode cross-section with bright ionomer phase and black Pt-covered areas, (b) distribution of ionomer film thicknesses before operation on an area of 1 x 1 µm 2 , and (c) dependence of tapping-mode measured current on Aquivion film thickness at room temperature. Figure 1

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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 score0.118
Threshold uncertainty score0.369

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 head0.013
GPT teacher head0.188
Teacher spread0.175 · 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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Citations1
Published2018
Admission routes1
Has abstractyes

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