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Record W2135342292 · doi:10.1002/celc.201402283

High‐Resolution Imaging of the Initial Stages of Oxidation of Cu(111) with Scanning Electrochemical Potential Microscopy

2014· article· en· W2135342292 on OpenAlexaff
Christoph Traunsteiner, Kaiyang Tu, Julia Kunze‐Liebhäuser

Bibliographic record

VenueChemElectroChem · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsUniversity of Saskatchewan
FundersTechnische Universität MünchenDeutsche Forschungsgemeinschaft
KeywordsScanning tunneling microscopeElectrochemical scanning tunneling microscopeScanning ion-conductance microscopyScanning electron microscopeElectrochemistryScanning probe microscopyScanning electrochemical microscopyElectrolyteElectrodeElectrochemical potentialMaterials scienceMicroscopyAnalytical Chemistry (journal)Electrode potentialScanning capacitance microscopyResolution (logic)ChemistryNanotechnologyScanning confocal electron microscopyScanning tunneling spectroscopyOpticsPhysicsPhysical chemistry

Abstract

fetched live from OpenAlex

Abstract Scanning electrochemical potential microscopy (SECPM) is a scanning probe technique for the detection of the electrochemical double‐layer (EDL) potential of a given working electrode (WE). We report the first high‐resolution imaging of the OH adsorbate structure formed on a Cu(111) WE in alkaline solution with SECPM, which reveals a structural parameter of (0.60±0.04) nm that is in excellent agreement with that found with electrochemical scanning tunneling microscopy. The origin of the potential used as a feedback signal in SECPM mode is discussed, focusing on leakage currents detected in the SECPM setup, faradaic reactions in the electrolyte, and electron‐tunneling processes between the tip and the WE. At potential set‐points that are typical for SECPM measurements, the potential detected with the tip is found to originate from a tunneling current. Therefore, the images recorded with SECPM cannot deliver information on the EDL potential at the WE surface in the present case.

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 score0.159
Threshold uncertainty score0.447

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 integrity0.0000.000
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 head0.004
GPT teacher head0.247
Teacher spread0.243 · 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

Citations4
Published2014
Admission routes1
Has abstractyes

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