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Record W4238071034 · doi:10.1149/ma2017-01/33/1584

Nanoscopic Ni Interfaced with Oxygen Conductive Supports: Link between Electrochemical and Catalytic Studies

2017· article· en· W4238071034 on OpenAlexaff
Yasmine M. Hajar, Mohamed S.E. Houache, Ubaidullah Tariq, P. Vernoux, Elena A. Baranova

Bibliographic record

VenueECS Meeting Abstracts · 2017
Typearticle
Languageen
FieldMaterials Science
TopicAdvancements in Solid Oxide Fuel Cells
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCatalysisMaterials scienceElectrochemistryElectrolyteFast ion conductorIonic bondingChemical engineeringNanoparticleInorganic chemistryYttria-stabilized zirconiaNanotechnologyChemistryElectrodeCeramicCubic zirconiaIonOrganic chemistryPhysical chemistry

Abstract

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Electrochemical promotion of catalysis (EPOC) or non-faradaic modification of catalytic activity (NEMCA) is a general phenomenon observed at the interface of solid-state electrochemistry and heterogeneous catalysis [1,2]. When the metal or metal oxide catalyst is interfaced with ionically conductive ceramic (solid electrolyte), the application of small electrical stimulus (current or potential) between the catalyst and a counter electrode results in occurrence of two parallel processes: (i) electrochemical reactions at the three phase boundary (tpb) and (ii) spillover/backspillover of ionic species to/from the solid electrolyte to the gas exposed catalyst surface. These ionic species act as promoters for the catalytic reaction and the promoted rate increase is several orders of magnitude higher than one predicted by Faraday’s law. The two most common promoters are Na+ cation from β″-Al2O3 and O2-anion provided from yttiria-stabilized-zirconia (YSZ) electrolyte. The existance of these ionic promoters was confirmed by a variety of surface science and electrochemical techniques [1]. The application of EPOC to nanoscopic, highly dispersed catalysts is of significant interest and represents one of the main challenges for practical application of this phenomenon [2, 3]. The goal of the present work is to investigate EPOC with Pt and Ru nanoparticles (2.5 nm average size) interfaced with YSZ (8% Y2O3-ZrO2) solid electrolyte for ethylene combustion reaction at T= 220 – 375 oC. To this end, the nanoparticles of Pt and Ru were synthesized using polyol method [4] and deposited on YSZ disk. Nanoparticles were subject to detailed electrochemical characterization to find the exchange current (Io) of electrochemical process at tpb and to link it to the apparent faradaic efficiency, |Λ| (eq. 1) and (2) defined in EPOC studies as [1]: |Λ| = Δr/(I/nF) (1) or |Λ| ≈ 2Fro/Io (2) where Δr (mol O/s) is the increase in the catalytic rate divided by the electrochemical rate, ro is the open circuit reaction rate, I/nF (n = 2 for O2-). The process is considered non-Faradaic if |Ʌ|is greater than 1. Figure 1 shows the transient reaction rate response of ethylene combustion over Pt nanoparticles under open circuit (U = 0 V) and under positive potentiostatic polarization (U = 0.5V) at 350 °C. Under closed circuit, the significant and reversible increase in the reaction rate is observed with the rate enhancement ratio r (ratio of the rate under closed circuit over the rate value at the open circuit) reaching 1.79 (i.e. 79 % increase) and the corresponding Faradaic efficiency, Ʌ, value of 23. This indicates that each O2-ion supplied to the Pt catalyst causes on average the catalytic reaction of 23 adsorbed O species originating from the gas phase. The effect of the applied constant potential and current, as well as partial pressure of ethylene, reaction temperature on EPOC effect for both Pt and Ru nanoparticles will be presented. The role of electrified nanoscopic interfaces on the extent of the rate increase will be discussed and rationalized using the exchange current density values [5]. References: 1. C. G. Vayenas, S. Bebelis, C. Pliangos, S. Brosda, D. Tsiplakides, Electrochemical Activation of Catalysis: Promotion, Electrochemical Promotion, and Metal-Support Interactions. Kluwer Academic/Plenum Publishers, 2001. 2. P Vernoux, L. Lizzaraga, A. De Lucas-Consuegra, J.-L. Valverde, S. Souentie, C. Vayenas, D. Tsiplakides, S. Balomenou, E.A. Baranova, Chem. Reviews. 113, 10, (2013) 8192 – 8260. 3. H.A.E. Dole, E.A. Baranova Implementation of Nano-structured Catalysts in the Electrochemical Promotion of Catalysis, in Handbook of Nanoelectrochemistry: Electrochemical Synthesis Methods, Properties, and Characterization Techniques. Aliofkhazraei, M., Makhlouf, A.S.H. (Eds.), Springer International Publishing, Switzerland (2015) 1095-1124. 4. E. A., Baranova, C. Bock, D. Ilin, D.Wang, B. MacDougall, Surf. Sci.600 (2006) 3502–3511. 5. H. A. E. Dole, L. F. Safady, S. Ntais, M. Couillard, E.A. Baranova, J. Catal.318 (2014) 85–94. Figure 1

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.316
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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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Published2017
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