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Enregistrement W4285497204 · doi:10.1149/ma2022-013503mtgabs

Analysis of Performance Degradation and Durability of the Air Cathode in an Alkaline Fuel Cell

2022· article· en· W4285497204 sur OpenAlexaff
Fatemeh ShakeriHosseinabad, Alireza Sadeghi Alavijeh, Shantanu Shukla, Mahmood Khalghollah, Simon Fan, Edward P.L. Roberts

Notice bibliographique

RevueECS Meeting Abstracts · 2022
Typearticle
Langueen
DomaineEngineering
ThématiqueFuel Cells and Related Materials
Établissements canadiensZincNyx Energy Solutions (Canada)University of Calgary
Organismes subventionnairesnon disponible
Mots-clésCathodeX-ray photoelectron spectroscopyDielectric spectroscopyElectrolyteMaterials scienceScanning electron microscopeDurabilityElectrodeElectrochemistryChemical engineeringPolarization (electrochemistry)Analytical Chemistry (journal)Raman spectroscopyComposite materialChemistryOpticsChromatography

Résumé

récupéré en direct d'OpenAlex

Degradation of the air cathodes is one of the key issues affecting the lifetime and durability of alkaline fuel cells and metal-air batteries. To prevent the ingress of electrolyte in the air cathode, modifying the hydrophobicity and thickness of the AL has been reported [1,2]. It was reported that increased hydrophobicity/thickness of the AL resulted in a decrease in the air cathode performance [1,2]. In this work, experimental in-situ and post-test analyses of the air cathode were applied to investigate the mechanism of performance degradation. In-situ methods including performance / lifetime analysis using a half-cell setup [3, 4], polarization studies, and electrochemical impedance spectroscopy (EIS) were used to investigate the electrochemical characteristics of the electrodes during operation. Post-mortem analysis methods included X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray computed tomography (X-ray CT), and Raman spectroscopy. The properties of pristine, conditioned, and failed air cathodes were characterized by these methods. Conditioning of air cathodes was performed by operating in half-cell utilizing 6 M KOH solution for 24 hours at 200 mA cm 2. The composition of the air cathode, operating conditions, and procedure for determining the performance and lifetime of the air cathode have been discussed in our previous work [3]. Cross-sectional SEM-EDX analysis was conducted on the air cathode to determine the amount of flooding/penetration of the electrolyte inside the active layers for electrodes prepared with 15, 25, and 40 wt% PTFE in the AL. Air cathodes were operated in the half-cell battery at 200 mA cm -2. EDX maps of the air cathodes showed that increasing the PTFE content leads to increased hydrophobicity and decreased depth of KOH penetration inside the AL after 5 hours of operation. However, air cathodes with higher PTFE content of 40 wt% exhibited a lifetime of only 48 hours, compared to > 150 hours for those containing 15 wt% and 25 wt% (conducted in a limited test duration). This could be due to decreased electrolyte content in the AL or blocking of pore space and active reaction sites [5], leading to higher local current densities and more rapid degradation. Cross-sectional EDX analysis indicated that electrolyte penetration/flooding inside the macrostructure of the backing layer (BL) was not observed in any of the electrodes. XPS was performed to reveal further information of the chemical states of the conditioned and failed cathodes [6]. XPS analysis indicated changes in the surface functional groups, in particular increasing hydroxyl groups in the failed cathodes, which may be indicative of reduced hydrophobicity of the carbon support. XPS analysis also indicated other changes in the chemical states of the catalyst, oxygen, fluorine and carbon after conditioning and failure of the air cathode. In-situ galvanostatic EIS was conducted during long-duration and accelerated stress tests to determine ohmic resistance, charge transfer resistance, and mass transfer limitation. The EIS data indicates that mass transfer resistance increased significantly after failure of the air cathode, confirming that oxygen transport to the catalyst was the cause of the poor performance of failed cathodes. Raman spectra and mapping was carried out to obtain additional information about changes in the AL after degradation. X-ray CT were conducted on air cathodes to determine the changes of pore structure, distribution of catalyst, PTFE and potassium. References: [1] Li, Y. S., Zhao, T. S., & Liang, Z. X. (2009). Effect of polymer binders in anode catalyst layer on performance of alkaline direct ethanol fuel cells. Journal of Power Sources, 190(2), 223-229. [2] Jo, J. H., Moon, S. K., & Yi, S. C. (2000). Simulation of influences of layer thicknesses in an alkaline fuel cell. Journal of applied electrochemistry, 30(9), 1023-1031. [3] ShakeriHosseinabad, F., SadeghiAlavijeh, A. , Khalghollah, M., Shukla, S., Fan, S., & Roberts, E. P. (2021, October). Mechanisms of Degradation of the Air Cathode in an Alkaline Fuel Cell. In ECS Meeting Abstracts (No. 40, p. 1217). IOP Publishing. [4] Endrődi, B., Samu, A., Kecsenovity, E., Halmágyi, T., Sebők, D., & Janáky, C. (2021). Operando cathode activation with alkali metal cations for high current density operation of water-fed zero-gap carbon dioxide electrolysers. Nature Energy, 6(4), 439-448. [5] Holdcroft, S. (2014). Fuel cell catalyst layers: a polymer science perspective. Chemistry of materials, 26(1), 381-393. [6] Guo, J., Kang, L., Lu, X., Zhao, S., Li, J., Shearing, P. R., ... & Parkin, I. P. (2021). Self-activated cathode substrates in rechargeable zinc–air batteries. Energy Storage Materials, 35, 530-537.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,003

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,000
Études des sciences et des technologies0,0000,000
Communication savante0,0010,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,203
Écart entre enseignants0,194 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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