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Record W3117444974 · doi:10.1149/ma2020-02372371mtgabs

(Invited) Effect of Water Management for Cathode Catalyst Layers Using a Non-Noble Metal Catalyst and a Novel Polymer Electrolyte on Cell Performance Hysteresis in Anion Exchange Membrane Fuel Cells

2020· article· en· W3117444974 on OpenAlexaff
Makoto Uchida, Kanji Otsuji, Naoki Yokota, Donald A. Tryk, Katsuyoshi Kakinuma, Kenji Miyatake

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsMD Precision (Canada)
Fundersnot available
KeywordsAnodePlatinumCatalysisElectrolyteCathodeNoble metalProton exchange membrane fuel cellElectrocatalystMembraneChemical engineeringMaterials scienceInorganic chemistryCarbon blackMembrane electrode assemblyDirect methanol fuel cellChemistryElectrodeIon exchangeElectrochemistryIonComposite materialOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

In this work, we examined the cell performance of membrane-electrode assemblies (MEAs), for anion exchange membrane fuel cells (AEMFCs), using a non-noble metal catalyst and a novel polymer electrolyte. The chemical structure of quaternized poly(arylene perfluoroalkylene), i.e., QPAF-4 (ion exchange capacity: IEC = 2.1 meq g -1 ) developed in this laboratory1 is shown in Figure 1. Since this membrane is soluble in methanol, it is also suitable for use as an electrode binder. The non-precious metal catalyst cell was loaded with 0.45 mg cm -2 Fe-N-C catalyst supplied by Pajarito Powder on the cathode and 0.20 mgPt cm -2 platinum catalyst on the anode. An MEA in which platinum was loaded (0.20 mgPt cm -2 ) on both the anode and cathode was prepared for comparison. Pt loaded on carbon black (Pt/CB, TEC10E50E), supplied from TKK Japan, was used as the platinum electrocatalyst. Figure 2 shows a comparison of Fe-N-C and Pt/CB for their I-V performances at 60 o C, 100% RH, 0 kPa g ; anode H 2 (100 mL/min); cathode O 2 (100 mL/min). The cell using the Fe-N-C catalyst exhibited large hysteresis in the I-V curve, i.e., a large difference in potential between increasing and decreasing current. Figure 3 shows a comparison of Fe-N-C and Pt/CB for their I-V performances at 60 o C, 100% RH, 100 kPa g ; anode H 2 (100 mL/min); cathode O 2 (100 mL/min). The hysteresis of the I-V performance for the cell using the Fe-N-C cathode decreased with increasing back pressure. The cell exhibited slightly lower open circuit voltage and similar IV performance compared with those using Pt/CB. At the present stage, the loading amount of Fe-N-C catalyst, ionomer content, and porosity of the catalyst layer have not yet been optimized. We investigated whether the hysteresis originates from the anode or cathode. Based on the results of various I-V measurements, we conclude that the hysteresis is related to water supplied to the cathode using the Fe-N-C catalyst. Further details will be given in this presentation. We found from these results that the water management is essential, due to its requirement for the cathode reaction, for high-performance AEMFCs. Finally, these results demonstrate the viability of the use of low-cost materials such as non-noble metal catalysts for the AEMFC. Acknowledgement This project was partly supported by NEDO Japan through funds for the “Advanced Research Program for Energy and Environmental Technologies” and the Japan Society for the Promotion of Science (JSPS) and the Swiss National Science Foundation (SNSF) under the Joint Research Projects (JRPs) program. References 1. H. Ono, T. Kimura, A. Takano, K. Asazawa, J. Miyake, J. Inukai, K. Miyatake, J. Mater. Chem. A, 5, 24804 (2017). Figure 1

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.199
Teacher spread0.188 · 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 teacher head, not a consensus.

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
Published2020
Admission routes1
Has abstractyes

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