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Record W2119969987 · doi:10.1002/celc.201500045

Electrooxidation of Ammonia at Tuned (100)Pt Surfaces by using Epitaxial Thin Films

2015· article· en· W2119969987 on OpenAlexaff
Jules Galipaud, Claudie Roy, Manuel H. Martin, Sébastien Garbarino, Lionel Roué, Daniel Guay

Bibliographic record

VenueChemElectroChem · 2015
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsEpitaxyUnderpotential depositionMaterials scienceCrystalliteX-ray photoelectron spectroscopyAnalytical Chemistry (journal)Thin filmPulsed laser depositionElectrochemistryLayer (electronics)CrystallographyElectrodeChemical engineeringMetallurgyChemistryCyclic voltammetryNanotechnologyPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Pt x Ni 100− x thin films (72≤ x ≤100, 10–25 nm thick) were deposited on MgO (100) substrates by using pulsed laser deposition. As shown from X‐ray diffraction analysis, the formation of a Pt(Ni) solid solution was observed over the Ni range investigated. All PtNi‐based films showed epitaxial growth in the (100) direction at 350 °C, which is in contrast to pure Pt films, where a Ni seeding layer was required to obtain epitaxial deposits at this temperature. X‐ray photoelectron spectroscopy depth‐profile analyses showed a Ni enrichment at the PtNi/MgO interface, which may be at the origin of the epitaxial growth in the alloys. After immersion in acidic media, Ni atoms are totally dissolved from the first ten atomic layers of the PtNi films, forming pure Pt electrodes. On the basis of underpotential‐deposited hydrogen electrochemical analyses, a (100) preferential surface orientation of the crystallites originating from epitaxial growth was confirmed on both Pt seeded and Pt x Ni 100− x films. It was shown that the fraction of (100) terraces and terrace edge sites are a determining factor in the electrooxidation of NH 3 . The highest electrocatalytic activity was observed with the Pt seeded film.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.241
Teacher spread0.222 · 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 teacher head, not a consensus.

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".

Quick stats

Citations21
Published2015
Admission routes1
Has abstractyes

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