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Record W1981791107 · doi:10.1021/la104497t

Switching Atomic Friction by Electrochemical Oxidation

2011· article· en· W1981791107 on OpenAlexaff
Aleksander Labuda, Florian Hausen, Nitya Nand Gosvami, Peter Grütter, R. Bruce Lennox, Roland Bennewitz

Bibliographic record

VenueLangmuir · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsElectrochemistryChemistryMaterials scienceChemical engineeringNanotechnologyElectrodePhysical chemistryEngineering

Abstract

fetched live from OpenAlex

Friction between the sliding tip of an atomic force microscope and a gold surface changes dramatically upon electrochemical oxidation of the gold surface. Atomic-scale variations of the lateral force reveal details of the friction mechanisms. Stick-slip motion with atomic periodicity on perfect Au(111) terraces exhibits extremely low friction and almost no dependence on load. Significant friction is observed only above a load threshold at which wear of the surface is initiated. In contrast, irregular stick-slip motion and a linear increase of friction with load are observed on electrochemically oxidized surfaces. The observations are discussed with reference to the amorphous structure of the oxo-hydroxide surface and atomic place exchange mechanisms upon oxidation. Reversible, fast switching between the two states of friction has been achieved in both perchloric and sulfuric acid solutions.

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 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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.008
GPT teacher head0.231
Teacher spread0.223 · 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".

Quick stats

Citations55
Published2011
Admission routes1
Has abstractyes

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