Structure, Properties, and Degradation of Ultrathin Ionomer Films in Fuel Cell Catalytic Layers
Notice bibliographique
Résumé
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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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».