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Enregistrement W4412541533 · doi:10.1149/ma2025-01473179mtgabs

Improving the Performance of High Temperature Steam Electrolysis Using Ceria-Modified Perovskite Electrodes

2025· article· en· W4412541533 sur OpenAlexaboutno aff
Batuhan Bal, Mykhailo Pidburtnyi, Viola Birss

Notice bibliographique

RevueECS Meeting Abstracts · 2025
Typearticle
Langueen
DomaineMaterials Science
ThématiqueAdvancements in Solid Oxide Fuel Cells
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésElectrolysisMaterials sciencePerovskite (structure)High-temperature electrolysisElectrodeChemical engineeringChemistryEngineeringElectrolyte

Résumé

récupéré en direct d'OpenAlex

Hydrogen production through steam electrolysis at high operating temperatures (ca. 800 °C) using solid oxide electrolysis cells (SOECs) offers significant advantages over low-temperature systems, due to their highly accelerated reaction kinetics and favorable thermodynamics. Traditionally used SOEC catalysts generally have a porous structure and consist of a mixture of electronically conducting Ni and ionically conducting yttria-stabilized zirconia (YSZ) (cermets). These systems rely on regions known as the triple phase boundary (TPB), where the electronically and ionically conducting phases and the reactant gas converge to facilitate steam electrolysis. However, prolonged exposure to high temperatures can lead to Ni particle oxidation, coarsening, and other microstructural changes, resulting in a decrease in TPB length. Therefore, our group has focused on the development and investigation of La₀.₃Ca₀.₇Fe₀.₇Cr₀.₃-δ (LCFCr) electrodes, which have a mixed ionic-electronic conducting (MIEC) perovskite structure (ABO₃). Since the entire surface of MIEC electrodes is then active towards steam electrolysis, they can operate without the need for TPBs. Our studies have shown that the LCFCr electrodes remain stable over a wide oxygen partial pressure range [1], making them a suitable candidate for symmetrical electrolyte-supported cell designs. However, while LCFCr electrodes have demonstrated very good performance under electrolysis and co-electrolysis conditions, their relatively low ionic conductivity still remains a barrier to achieving excellent efficiency during steam electrolysis. To address this limitation in other perovskite catalysts powders, such as La0.6Sr0.4Co0.2Fe0.8O3−δ (LSCF), ionically conducting samaria-doped ceria (SDC) powder was mixed in with LSCF to enhance both CO2 and water electrolysis[2,3]. In our group, SDC infiltration and co-infiltration of SDC and LCFCr phases into the LCFCr backbone [4] were both investigated, initially for use as an air electrode. However, SDC infiltration tends to block catalytically active sites by forming a dense and continuous coating that hinders gas diffusion to the underlying active MIEC surface, leading to an increase in the low frequency resistance. In contrast, co-infiltration creates a more balanced microstructure that preserves the MIEC active sites while also enhancing ionic conductivity. However, the performance of infiltrated LCFCr-parent backbones has not been investigated previously under either steam electrolysis or co-electrolysis conditions. In this study, low-surface-area 20% mol samaria-doped ceria (SDC20) powders were mechanically mixed with LCFCr-parent powders at a 50 wt% ratio to both enhance the ionic conductivity of parent LCFCr electrodes while preventing the blockage of active sites. In order to evaluate their performance, composite LCFCr–SDC20 electrodes were placed onto both sides of a trilayer SDC/YSZ/SDC electrolyte via blade coating. Electrochemical evaluation of the ‘fuel electrode’ was performed under varying H₂O:H₂ gas mixtures at 800 °C using cyclic voltammetry, impedance spectroscopy, and chronoamperometry techniques via a three-electrode configuration. In 3-electrode configuration, a reference electrode (RE) placed on the air side and the electrochemical experiments were performed to understand working electrode (WE) performance under ‘fuel’ flow. After a performance survey, the WE was exposed to a voltage of -1.3 V vs RE for 6 hours to investigate their short-term stability in the electrolysis mode. Under operating conditions of 90 vol% steam/10% H2 at 800 °C, the composite LCFCr–SDC20 cathodes exhibited polarization resistance values at 1.3 V vs RE comparable to LCFCr-parent cathodes (0.18 vs. 0.17 Ω·cm²), while at a cell voltage of -1.3 V vs RE, the LCFCr-parent cathodes initially showed a current density of ~650 mA/cm², whereas the LCFCr–SDC20 composite cathodes gave a current density of 690 mA/cm². After being held at -1.3 V for 6 hours, the current density of LCFCr-parent cathodes increased to 670 mA/cm², while that of the composite cathodes increased to ca. 740 mA/cm², demonstrating that the performance of the composite cathodes improved with time under these operating conditions. Acknowledgements The authors would like to thank the Natural Sciences and Engineering Research Council of Canada (NSERC CRNSG) and the Global Hydrogen Production Technologies (HyPT) Research Center for funding of this research. We also thank Drs. Anand Singh and Scott Paulson for helpful discussions. References [1] A. S. Bass, A. C. Singh, S. Paulson, and V. I. Birss, ECS Meeting Abstracts, MA2023-02, 2238 (2023). [2] Z. Huang, H. Qi, Z. Zhao, L. Shang, B. Tu, and M. Cheng, J. Power Sources, 434, 226730 (2019). [3] K. J. Lee, M. J. Lee, S. H. Park, and H. J. Hwang, J. Korean Ceram. Soc., 53, 489 (2016). [4] B. Molero-Sánchez, P. Addo, A. Buyukaksoy, and V. Birss, J. Electrochem. Soc., 164, F3123 (2017).

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)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
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 GPT0,248
Écart entre enseignants0,239 · 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
Publié2025
Routes d'admission1
Résumé présentoui

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