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Record W2089100894 · doi:10.1021/jp900478u

Effect of Temperature Variation on the Under-Potential Deposition of Copper on Pt(111) in Aqueous H<sub>2</sub>SO<sub>4</sub>

2009· article· en· W2089100894 on OpenAlexaff
Gregory Jerkiewicz, Frédéric Perreault, Zorana Radovic-Hrapovic

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2009
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsQueen's UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsCopperAnalytical Chemistry (journal)ChemistryDeposition (geology)Aqueous solutionCharge densityStripping (fiber)Atmospheric temperature rangeAnodic stripping voltammetryElectrochemistryMaterials scienceElectrodePhysical chemistryThermodynamics

Abstract

fetched live from OpenAlex

The under-potential deposition of copper on Pt(111) from aqueous 0.05 M H 2 SO 4 + 5 mM CuSO 4 ·5H 2 O is studied in the 273 ≤ T ≤ 333 K range using cyclic voltammetry (CV). The CV transients always reveal two cathodic peaks (C I and C II ) for the entire temperature range; there is only one anodic peak (A I ) in the case of 273 ≤ T < 298 K and the second one appears in the case of T ≥ 298 K. In the case of 273 ≤ T < 298 K, the cathodic and anodic peaks shift toward lower potentials upon T increase, while in the case of T ≥ 298 K, there is no observable peak displacement. The charge density associated with the Cu UPD deposition and stripping does not reveal any temperature-dependence. The results demonstrate that T variation does not lead to charge-density redistribution between the peaks, but the charge density of the first peak (C I and A I ) in the deposition-stripping profiles is always greater than that of the second peak (C II and A II ). The experimentally determined charge density associated with the Cu deposition and stripping is lower than the value expected for one epitaxial Cu UPD layer on Pt(111). This difference is due to the coadsorption of anions that occurs concurrently with UPD Cu.

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 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 score0.002
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.003
GPT teacher head0.213
Teacher spread0.210 · 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.

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".

Quick stats

Citations17
Published2009
Admission routes1
Has abstractyes

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