Correlative X-Ray Tomographic Imaging of Catalyst Layer Degradation in Fuel Cells
Notice bibliographique
Résumé
Performance optimization of polymer electrolyte fuel cells (PEFCs) require precise design and knowledge of the porous catalyst layer (CL) structure. Furthermore, understanding the changes to this structure due to degradation is important for performance retention and durability. Hence, there is a need to characterize these porous networks using advanced imaging techniques with multi-scale resolution. Scanning electron microscopy (SEM) have typically been used for characterizing CL as it provides high contrast and high-resolution imaging.[1] However, SEM alone is limited to 2D visualization, requiring considerable sample handling and preparation, and can suffer from edge effects and large depth of focus; making segmentation and interpretation of pores difficult. By combining SEM with focused ion beam (FIB) milling, a three-dimensional visualization can be acquired by eroding a layer of material using an ion beam and imaging the newly exposed surface to obtain a stack of 2D images through the thickness of the material. In contrast, the use of X-ray computed tomography (XCT) allows for three-dimensional imaging with symmetric resolution by volumetric imaging and is non-intrusive where the sample is intact post imaging. Studies focusing on PEFC degradation using XCT have primarily addressed macro-scale changes with recent work also contributing operando imaging to obtain water distribution changes within the gas diffusion layer (GDL) using micro-XCT. [2-6] However, the dynamic and locally variable nature of catalyst layer degradation demands the use of correlative imaging procedures for nano-XCT analysis. In the present work, a correlative workflow is developed for X-ray tomographic imaging of cathode catalyst layer degradation featuring four-dimensional (3D plus time) operando imaging and ex situ nano-scale imaging (Fig. 1). 4D operando imaging shows high water content observed under the lands and near the surface of the cathode GDL. Macro imaging results show that the catalyst layer solid area fraction is gradually reduced by 25% with crack formation and severe corrosion at the edges of the solid phase. In addition, the thickness is found to decrease by 50%, a similar trend to the measured electrochemical surface area. Localized degradation features such as nano-scale cracks and internal pore-size distribution changes are resolved using nano-XCT and tracked by 3+1D imaging at different stages of degradation. Porosity loss quantified by XCT on the order of 40% from beginning-of-life to end-of-life with reduction in connected pore fraction are observed as well as an increase in average pore size by 50%. The effect of changes at the nano-scale on diffusion properties are also calculated and an empirical model is proposed for these types of catalyst layer structures where Knudsen effects are dominant. Overall, the new findings from this work demonstrate important linkages between CL structure, transport properties, liquid water flooding, and fuel cell performance in the context of degradation. The workflow and analysis methods could henceforth be contemplated when employing computational modeling and catalyst layer design studies where correlation to fuel cell performance and durability is desired. 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. This research was undertaken, in part, thanks to funding from the Canada Research Chairs program. We also thank 4D LABS at Simon Fraser University for technical assistance during FIB/SEM liftout procedure. References [1] A. Tavassoli et al. J. Power Sources 322 (2016) 17-25 [2] R.T. White et al. J. Power Sources 350 (2017) 94-102 [3] Y. Singh et al. J. Power Sources 345 (2017) 1–11 [4] D Ramani et al. J. Electrochem. Soc. 165 (2018) F3200-08 [5] Y. Singh et al. J. Electrochem. Soc. 164 (2017) F1331-41 [6] R.T. White et al. Sci. Rep. 9 (2019) 1843 Figure 1: a) Wedge shaped MEA sample imaged by micro-XCT for morphological quantification and screening of the cathode catalyst layer to find a representative area to perform FIB liftout before subsequent imaging using nano- XCT. b) 2D cross-sectional planes virtually extracted from the 3D volume in (a). c) FIB lift-out needle attached to the sample using Pt deposition for sample lift-off; the lifted sample is then placed on a pin tip. d) 3D rendering of the selected catalyst layer region imaged using nano-XCT with porosity volume segmentation shown in orange. Figure 1
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».