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Enregistrement W4386853708 · doi:10.1149/ma2023-01362110mtgabs

A Study on Effect of Ionomer Content on Catalyst Ink Property and PEM Water Electrolyzer Performance

2023· article· en· W4386853708 sur OpenAlex

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Notice bibliographique

RevueECS Meeting Abstracts · 2023
Typearticle
Langueen
DomaineEnergy
ThématiqueHybrid Renewable Energy Systems
Établissements canadiensNational Research Council Canada
Organismes subventionnairesnon disponible
Mots-clésIonomerNafionProton exchange membrane fuel cellElectrolysis of waterMaterials scienceCatalysisElectrolysisChemical engineeringMembrane electrode assemblyElectrolytePolymer electrolyte membrane electrolysisSolventMembraneChemistryComposite materialElectrochemistryPolymerElectrodeOrganic chemistryCopolymer

Résumé

récupéré en direct d'OpenAlex

Producing hydrogen from water electrolysis with renewable electricity is essential for a carbon-free and environment-friendly economy. Proton exchange membrane (PEM) water electrolysis has advantages over other types of water electrolysis technologies with respect to compact system, high purity H 2 , high current density operation, better safety and reliability etc. Catalyst coated membrane (CCM) is the core of the membrane electrode assembly (MEA) and PEM water electrolyzer [1]. The CCMs are prepared by depositing catalyst inks onto the polymer electrolyte membrane. The composition of the catalyst inks plays an important role in determining the CCM and PEMWE performance. Catalyst ink is prepared from catalyst, ionomer and solvent. Commonly used is IrO x as catalyst, Nafion solution as ionomer (binder and proton conductivity path), and a mixture of organic solvent and water as solvent. One of the key parameters determining the CCM performance is the ionomer content in the catalyst layer. A wide range of ionomer content was reported in the literature, ranging from 2 to 30wt%. Xu et al. reported an optimal value of 25 wt% ionomer content using Ru 0.7 Ir 0.3 O 2 [1]. The same Nafion content was used by Su et al. with IrO 2 [2]. Bernt and Gasteiger found 11.6 wt% ionomer content showed the best performance with IrO 2 /TiO 2 [3]. Ma et al. concluded that 30 wt% ionomer content was the best using Ir black [4]. P. Holzapfel et al [5] and S. Khandavali et al [6] used 2 wt% of ionomer content in their studies with IrO 2 . The large variability of the ionomer content indicates that there is a need on fundamental understanding of the effect of ionomer content for PEMWE applications. Catalyst ink properties may affect the catalyst layer structure and further PEMWE performance. S. Khandavali et al. studied the rheology and microstructure of the catalyst inks [7]. However, no further steps were presented such as fabricating CCMs using the ink and testing the CCMs in PEMWE. How the ink properties affect the catalyst layer structure, and further the PEMWE performance are not studied to our knowledge. In this work, a study on effect of ionomer content on catalyst ink property and further PEMWE performance is presented. In this work, catalyst ink was prepared from a mixture of isopropanol and water (1:1), Nafion solution, and IrO 2 . Inks with Nafion concentrations ranging from 1.0 wt. % to 20 wt. % were investigated. Ink properties such as viscosity, Zeta-potential and average particle size were studied. Properties of CCMs developed from the inks by directly coating the catalyst ink on Nafion membrane using ultrasonic spray were also investigated. The CCMs prepared from inks with 5.0, 7.0, 8.5 and 10% Nafion were tested in PEM water electrolyzer single cell at 80 o C and ambient pressure. The CCM with the 7.0% Nafion shows the highest performance, while the 5.0% Nafion shows the lowest. The 8.5 and 10% Nafion CCMs show slightly lower performance than the 7.0%. The PEMWE was diagnosed with AC impedance. Fig. 1 presents the EIS spectra of the four CCMs in PEMWE obtained at 50 mA.cm -2 . It can be seen that other than the CCM with 5.0% Nafion, all other 3 CCMs showed similar spectra. This is in agreement with the polarization curves. Impedance data fitting using the modified Randles equivalent circuit (solid lines in Fig. 1) shows that the 5.0% Nafion demonstrated the highest anode charge transfer resistance (oxygen evolution reaction (OER)) and the 7.0% shows the lowest value. Correlation of the ink properties with the PEMWE performance will be presented. References Xu, K. Scott, Int. J. Hydrogen Energy, 35 (2010) 12029 – 12037 Su, B. J. Bladergroen, V. Linkov, S. Pasupathi, S. Ji, Int. J. Hydrogen Energy, 36 (2011) 1615081 – 15088 Bernt, H. Gasteiger, J. Electrochem. Soc., 163 (11) (2016) F3179 – F3189 Ma, S. Sui, Y. Zhai, Int. J. Hydrogen Energy, 34 (2009) 678 – 684 Holzapfel, M. Bühler, C. V. Pham, F. Hegge, T. Böhm, D. McLaughlin, M. Breitwieser, S. Thiele, Electrochem. Commun. 110 (2020) 106640 Buhler, P. Holzapfel, D. McLaughlin, S. Thiele, J. Electrochem. Soc., 166 (14) (2019) F1070 – F1078 Khandavali, J. H. Park, N. N. Nariuki, S. F. Zaccarine, S. Pylypenko, D. J. Myers, M. Ulsh, S. A. Mauger, ACS Appl. Mater. Interfaces, 11 (2019) 45068 – 45079 Figure 1

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut 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 enseignants0,453
Score d'incertitude au seuil0,623

Scores Codex et Gemma par catégorie

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

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 Opus0,027
Tête enseignante GPT0,237
Écart entre enseignants0,210 · 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