Fabrication and Characterization of Electrospun Electrodes for Flow Battery Applications
Notice bibliographique
Résumé
Flow batteries are a promising candidate for grid-level energy storage, due to their decoupled power generation and energy storage [1]. Since they were first proposed by NASA in the 1970’s [2], numerous prototypes have been shown, but commercialization has been hindered by their suboptimal design and high cost. Most research in this field has been focused on adjusting redox chemistry or improving catalytic properties of the electrode. Less effort has been made in addressing the mass transport within the electrochemical cell. The electrode is typically a porous carbon material which supports redox reactions on its surface [1]. Optimizing the hydrodynamic conditions and transport phenomena via structural modifications of the electrode is a promising option to improve cell performance. Fibrous materials are of special interest due to their high surface area, which leads to a higher reaction rate, while at the same time being highly porous to provide good permeability and diffusivity. In this work, a range of fibrous electrodes were produced by electrospinning of polyacrylicnitrile (PAN) followed by carbonization. Electrospinning is a convenient method for making prototype materials since it allows tremendous flexibility in the final product by simply varying processing parameters [3]. The use of novel electrodes to improve mass transport and reactive surface area in flow batteries has started to be the focus of investigations [4], but recent modeling work [5] has shown that significant improvements can be made. Materials were produced with a range of fiber morphology, porosity, pore sizes, and thickness. SEM images of 1 specific electrospun material before and after carbonization are shown in figure 1. In addition to these structural measurements, key transport properties such as diffusivity and permeability were also measured and found to vary widely between materials. It is expected that these properties will correlate closely with cell performance, hence proper characterization of transport parameters will be essential to the further optimization of high performance materials. [1] A. Z. Weber, M. M. Mench, J. P. Meyers, P. N. Ross, J. T. Gostick, and Q. Liu, “Redox flow batteries: a review,” J. Appl. Electrochem. , vol. 41, no. 10, pp. 1137–1164, Sep. 2011. [2] L. H. Thaller, “Electrically rechargeable REDOX flow cell,” US3996064 A, 07-Dec-1976. [3] B. Zhang, F. Kang, J.-M. Tarascon, and J.-K. Kim, “Recent advances in electrospun carbon nanofibers and their application in electrochemical energy storage,” Prog. Mater. Sci. , vol. 76, pp. 319–380, Mar. 2016. [4] G. Lin, P. Y. Chong, V. Yarlagadda, T. V. Nguyen, R. J. Wycisk, P. N. Pintauro, M. Bates, S. Mukerjee, M. C. Tucker, and A. Z. Weber, “Advanced Hydrogen-Bromine Flow Batteries with Improved Efficiency, Durability and Cost,” J. Electrochem. Soc. , vol. 163, no. 1, pp. A5049–A5056, Jan. 2016. [5] M. D. R. Kok and J. T. Gostick, “Multiphysics Simulation of the Bromine Cathode: Cell Architecture and Electrode Optimization,” ECS Trans. , vol. 69, no. 1, pp. 21–35, Sep. 2015. 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 ».