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Enregistrement W4230223765 · doi:10.1149/ma2014-01/16/719

Improved Catalytic Reactor for the Electrochemical Promotion of Highly Dispersed Ru Nanoparticles with CeO<sub>2</sub> Support

2014· article· en· W4230223765 sur OpenAlexaff
Holly A. E. Dole, Luís Felipe Safady, Spyridon Ntais, Martin Couillard, Elena A. Baranova

Notice bibliographique

RevueECS Meeting Abstracts · 2014
Typearticle
Langueen
DomaineEnergy
ThématiqueElectrocatalysts for Energy Conversion
Établissements canadiensNational Research Council CanadaUniversity of Ottawa
Organismes subventionnairesnon disponible
Mots-clésCatalysisMaterials scienceElectrolyteElectrochemistryChemical engineeringYttria-stabilized zirconiaStoichiometryIonic bondingNanoparticleInorganic chemistryElectrodeNanotechnologyCubic zirconiaChemistryComposite materialPhysical chemistryIon

Résumé

récupéré en direct d'OpenAlex

Electrochemical promotion of catalysis (EPOC) is a promising method for enhancing catalytic activity through the application of a small electrical stimulus between the catalyst-working and counter electrode deposited on a solid electrolyte 1 . The electronic properties of the catalyst can be modified resulting in a change in catalytic activity. In the case of yttria-stabilized zirconia (YSZ) as a solid electrolyte, the addition or removal of O 2- species on the catalyst surface can be controlled in situ depending on the specified reaction conditions. Fully reversible and “permanent” or “persistent” EPOC has been reported for more than 70 various catalytic systems 1 . In reversible EPOC experiments, the reaction rate returns to its initial value after the electrical stimulus is interrupted. For permanent EPOC (P-EPOC), the reaction rate remains at a higher value than the initial open circuit value 2,3 . Despite receiving much attention, this phenomenon has not yet reached commercial application. One of the main technical factors preventing such development is the use of thick film catalysts with low surface areas and high material costs 4 . Ceria, CeO 2 , is a mixed ionic-electronic conducting (MIEC) material that conducts O 2- due to oxygen vacancies in the crystallographic structure in addition to conducting electrons at elevated temperatures. Furthermore, due to its non-stoichiometry, CeO 2 has the ability to undergo conversion between Ce 4+ and Ce 3+ quite easily 5 . These properties make the use of ceria-containing catalysts of interest for many applications. In heterogeneous catalysis, Pt group metals deposited on CeO 2 show a metal-support interaction (MSI) effect associated with charge transfer between the two solids that are in contact. In EPOC studies, using a MIEC can also ensure electrical connectivity between highly dispersed nanoparticle catalysts 6 . In this study, electrochemical enhancement of catalytic activity of a low particle size (1.9 nm) ruthenium nanoparticles catalyst for ethylene oxidation was investigated. Ru nanoparticles, synthesized using a modified polyol reduction method, were supported on CeO 2 resulting in a 1 wt% Ru loading (RuNPs/CeO 2 ) (i.e., typical in heterogeneous catalysis studies).The highly dispersed RuNPs/CeO 2 catalyst powder was supported on a YSZ solid electrolyte in order to apply polarization. The discussion of this study includes the effect of the partial pressure of ethylene with constant partial pressure of oxygen, temperature, and applied positive and negative current on the catalytic activity of the RuNPs/CeO 2 catalyst as well as the role of the cerium redox state in the observed persistent effect. In addition, the catalytic properties of the RuNPs/CeO 2 catalyst is compared to that of larger Ru particles supported on CeO 2 (TD-Ru/CeO 2 ) (same metal loading) and blank CeO 2 , both supported on a YSZ solid electrolyte. Characterizations of the catalysts were carried out using TEM and SEM. In addition, XPS analysis was done for the RuNPs/CeO 2 catalyst as prepared and “spent” (after the reaction). Overall, it was observed that only the RuNPs/CeO 2 catalyst could be catalytically enhanced, showing a pronounced enhancement (up to 2.5 times) of the catalytic rate for negative polarization. The opposite effect was observed for positive polarization. This effect of both positive and negative polarization is illustrated by Fig.1. Fig. 1. Transient effect of current application for C 2 H 4 oxidation over Ru/CeO 2 on YSZ electrolyte at 350°C for an applied current of -2 μA for 4 hours and +2 μA for 6 hours (0.012 kPa C 2 H 4 ). Apparent Faradaic efficiencies up to 100 were also determined, indicating a non-Faradaic effect. In addition, a persistent effect was observed, showing stability up to 16 hours after current interruption. The modification of the cerium oxidation state (i.e., reduction from Ce 4+ to Ce 3+ ) is proposed to enhancethe catalytic performance of the Ru nanoparticles. This is due to the presence of more oxygen vacancies in the ceria interlayer causing a stronger metal-support interaction.These results demonstrate the feasibility of in-situ modification of the metal support-interaction between Ru nanoparticles and CeO 2 catalytic support. References 1. C. G. Vayenas, S. Bebelis, C. Pliangos, S. Brosda, and D. Tsiplakides, Electrochemical Activation of Catalysis: Promotion, Electrochemical Promotion, and Metal-Support Interactions , Kluwer Academic/Plenum Publishers, New York, (2001). 2. J. Nicole and C. Comninellis, J. Appl. Electrochem. , 28 , 223–226 (1998). 3. S. Wodiunig, V. Patsis, and C. Comninellis, Solid State Ionics , 137 , 813–817 (2000). 4. D. Tsiplakides and S. Balomenou, Catal. Today , 146 , 312–318 (2009). 5. A. Trovarelli, Ed., Catalysis by Ceria and Related Materials , Imperial College Press, London, (2002). 6. A. Kambolis et al., Electrochem. commun. , 19 , 5–8 (2012).

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 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)0,001
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 enseignants0,004
Score d'incertitude au seuil0,801

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
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 savante0,0000,000
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 Opus0,007
Tête enseignante GPT0,203
Écart entre enseignants0,196 · 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 tête enseignante, 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

Citations2
Publié2014
Routes d'admission1
Résumé présentoui

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