Novel Method for Measuring in-Plane Effective Diffusivity of Ultrathin Catalyst Layer for PEMFC
Notice bibliographique
Résumé
Fuel cells are being increasingly deployed in various applications, however like all emerging technologies, its cost still needs to be lowered for wider commercialization. The most expensive component is the noble platinum (Pt) catalyst, so reducing the amount of Pt remains an ongoing effort. There are two ways to approach this problem: find a cheaper alternative1,2 or use less Pt.3,4 Regarding the former, most candidates are less active than Pt, so require higher loading and thicker catalyst layers, while the latter case, the lower loading must be compensated by higher accessibility and utilization. In both cases it is essential to design improved catalyst layer (CL) structures to provide maximum accessibility of reactant to the catalytic sites.5 Characterizing the nanoporous structure of the CL in terms of transport processes is essential to understanding how to design a better layer. The key transport parameter in fuel cell operation is the effective diffusivity through the CL structure since diffusion is the primary mode of reactant transport. Despite the importance of characterizing the effective diffusivity of the CL, the thinness of the CL combined with the fact that it’s not self-supporting, has hindered the development of well-established, easy to apply, and standardized tool and only a limited number of technique is available.6 There are several requirements in designing the proper ex-situ effective diffusivity measurement experiment for the CL. First, any surface in contact with the sample must be scratch-free to eliminate additional diffusion pathways. Second, the need for sealing should be avoided as it is nearly impossible to properly seal such thin (~10µm) layer. Lastly, the experiment should be designed so that it is performed within a reasonable time. This work presents a new method building on previous work7,8, but using a radial geometry instead. The main advantage of the method is that it requires no sealing around the edge of the sample, therefore easily applied even to ultrathin porous layers. Inside a cylindrical chamber, the catalyst layer sample is placed between two circular pedestals and the oxygen concentration is measured at the center as shown in Figure 1(a). The sample is initially flushed with air, then nitrogen gas is flowed past the sample perimeter at high flow rate to ensure instant change in boundary condition. The depletion of the oxygen concentration at the center of the sample is measured and recorded as a function of time. The effective diffusivity is determined by fitting the analytical solution of the Fick’s second law in cylindrical coordinates to the transient oxygen concentration profile.9 The technique was validated against open air and known GDL materials.7,8 In the present study, this novel experimental technique was applied to ultrathin porous layers fabricated with different ink formulae to explore the impact of morphology, and strong differences were seen. References: M. Lefèvre, E. Proietti, F. Jaouen, and J.-P. Dodelet, Science (80-. )., 324, 71–74 (2009) E. Proietti et al., Nat. Commun., 2, 416 (2011) S. Martin, B. Martinez-Vazquez, P. L. Garcia-Ybarra, and J. L. Castillo, J. Power Sources, 229, 179–184 (2013) S. Shukla, K. Domican, and M. Secanell, ECS Trans., 69, 761–772 (2015). Y. Tabe, M. Nishino, H. Takamatsu, and T. Chikahisa, J. Electrochem. Soc., 158, B1246 (2011) Z. Yu and R. N. Carter, J. Power Sources, 195, 1079–1084 (2010). R. Rashapov, F. Imami, and J. T. Gostick, Int. J. Heat Mass Transf., 85, 367–374 (2015) R. R. Rashapov and J. T. Gostick, Transp. Porous Media, 115, 1–23 (2016). J. Crank, (1975) "The Mathematics of Diffusion". 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) | 0,001 | 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 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».