Electrochemical Promotion of Bimetallic Nanoparticles with Low-Noble Metal Content Interfaced with Yttria-Stabilized Zirconia Solid-Electrolyte
Notice bibliographique
Résumé
Heterogeneous catalysts play a central role in production of a variety of useful chemicals, energy generation and greenhouse gas emissions reduction. A heterogeneous catalyst usually consists of fine metal or metal oxide particles in the nanometer range dispersed on a high surface area supports. The catalytic activity and/or selectivity of the catalyst could be tuned in by using chemical promoters that are added to the catalyst during its fabrication or by choosing a suitable catalyst supports via metal-support interaction (MSI) effect. Another way to efficiently promote catalytic activity and in some instances catalyst selectivity is the use of electrochemistry via Electrochemical Promotion of Catalysis (EPOC), also called Non-faradaic Electrochemical Modification of Catalytic Activity (NEMCA) phenomenon [1, 2]. EPOC or NEMCA is ascribed to significant changes in the catalytic properties of metal or metal oxide catalysts deposited on solid-electrolytes caused by the application of small current (in the range of a few μA) or potential (up to 2V). The application of electric stimuli results in the supply of ionic species from the solid-electrolyte to the active surface, where the catalytic reaction takes place. These ionic species act as promotes and their addition results in significant catalytic rate increase due to changes in the catalyst work function [2-4]. This phenomenon has been applied to over 100 catalytic systems and reactions and continues to make an impact to surface science, catalysis and solid-state electrochemistry. The application of EPOC to nanostructured, highly dispersed catalysts has attracted significant interest in the last decade and several studies have demonstrated dramatic EPOC effect with noble metal (Pt, RuO2, Pd, etc.) nanoparticles (NPs) as low as 1.5 nm in size and metal loading down to 0.1 mg metal/cm2 [5-9]. Despite this tremendous progress, further improvement in metal utilization for practical advancement of EPOC is essential. In the present work, we investigated EPOC of bi-metallic, highly dispersed Ni90Pd10 and Ru45Fe55 (at. %) nanoparticles for two environmentally important reactions: CH4 combustion and CO2 hydrogenation. Both CH4 and CO2 are greenhouse gases that have negative impact on the environment and contribute to climate change, therefore methane conversion to CO2 and CO2 transformed to useful chemicals have several advantages. Ni90Pd10 and Ru45Fe55 NPs were synthesized using polyol reduction method by using ethylene glycol as reducing and stabilizing agent. TEM/SEM and XRD analysis were carried out to determent the particle and crystallite size, as well as alloy formation in bi-metallic NPs. The resulting colloidal solution containing NPs were deposited on yttria-stabilized zirconia (8 mol % Y2O3-ZrO2, (YSZ)) solid-electrolyte disk (D = 19 mm, thickness = 1 mm) with loading of 0.2 - 0.3 mg metal/cm2 and served as a catalyst-working electrode. Inert gold counter and pseudo-reference electrode were deposited on the opposite side of YSZ disk. Gold mesh served a current collector for NPs. The solid-electrolyte cell was placed in the CSTR-type quartz reactor (atm. pressure) [9] for CH4 combustion (T = 400 – 500 oC) and CO2 hydrogenation (T = 275 – 400 oC) reactions. Galvanostatic and potentiostatic EPOC transient experiments were carried out under various gas compositions and temperatures. The EPOC results on bi-metallic nanoparticles will be presented and the role of Ni and Fe on the catalytic activity and EPOC efficiency will be discussed. References Stoukides, C.G. Vayenas, J. Catal., 70 (1981), 137-146 G. Vayenas, S. Bebelis, S. Ladas, Nature 343 (1990) 625–627. G. Vayenas, S. Bebelis, C. Pliangos, S. Brosda, D. TsiplakidesElectrochemical Activation of Catalysis: Promotion, Electrochemical Promotion and Metal-support Interactions, Kluwer Academic/Plenum, New York (2001) Vernoux, L. Lizarraga, M.N. Tsampas, F.M. Sapountzi, A. De Lucas-Consuegra, J.L. Valverde, S. Souentie, C.G. Vayenas, D. Tsiplakides, S. Balomenou, E.A. Baranova, Chem. Rev. 113 (2013) 8192–8260. Kambolis, L. Lizarraga, M.N. Tsampas, L. Burel, M. Rieu, J.P. Viricelle, Vernoux Electrochem. Commun., 19 (2012), pp. 5-8. A.E. Dole, E.A. Baranova, Implementation of Nanostructured Catalysts in the Electrochemical Promotion of Catalysis in Handb. Nanoelectrochemistry M. Aliofkhazraei, H.A.S. Makhlouf (Eds.), Springer International Publishing, Cham (2015), 1-27 A.E. Dole, A. Costa, M. Couillard, E.A. Baranova, J. Catal. 333 (2016) 40–50. M. Hajar, K.D. Patel, U. Tariq, E.A. Baranova, J. Catal. 352 (2017) 42–51.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».