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Record 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 on OpenAlexaff
Fatemeh ShakeriHosseinabad, Alireza Sadeghi Alavijeh, Shantanu Shukla, Mahmood Khalghollah, Simon Fan, Edward P.L. Roberts

Bibliographic record

VenueECS Meeting Abstracts · 2022
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsZincNyx Energy Solutions (Canada)University of Calgary
Fundersnot available
KeywordsCathodeX-ray photoelectron spectroscopyDielectric spectroscopyElectrolyteMaterials scienceScanning electron microscopeDurabilityElectrodeElectrochemistryChemical engineeringPolarization (electrochemistry)Analytical Chemistry (journal)Raman spectroscopyComposite materialChemistryOpticsChromatography

Abstract

fetched live from 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.203
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2022
Admission routes1
Has abstractyes

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