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Record W2040916793 · doi:10.1063/1.3470107

High-resolution friction force microscopy under electrochemical control

2010· article· en· W2040916793 on OpenAlexaff
Aleksander Labuda, William Paul, Brendan Pietrobon, R. Bruce Lennox, Peter Grütter, Roland Bennewitz

Bibliographic record

VenueReview of Scientific Instruments · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsElectrochemical noiseMaterials scienceContext (archaeology)Atomic force microscopyMicroscopeNanotechnologyOpticsElectrochemistryPhysicsElectrode

Abstract

fetched live from OpenAlex

We report the design and development of a friction force microscope for high-resolution studies in electrochemical environments. The design choices are motivated by the experimental requirements of atomic-scale friction measurements in liquids. The noise of the system is analyzed based on a methodology for the quantification of all the noise sources. The quantitative contribution of each noise source is analyzed in a series of lateral force measurements. Normal force detection is demonstrated in a study of the solvation potential in a confined liquid, octamethylcyclotetrasiloxane. The limitations of the timing resolution of the instrument are discussed in the context of an atomic stick-slip measurement. The instrument is capable of studying the atomic friction contrast between a bare Au(111) surface and a copper monolayer deposited at underpotential conditions in perchloric acid.

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)0.001
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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.006
GPT teacher head0.272
Teacher spread0.266 · 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

Citations39
Published2010
Admission routes1
Has abstractyes

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