MétaCan
Menu
Back to cohort
Record W2044928750 · doi:10.1063/1.4903484

Accurate formula for dissipative interaction in frequency modulation atomic force microscopy

2014· article· en· W2044928750 on OpenAlexaff
Kazuhiro Suzuki, Kei Kobayashi, Aleksander Labuda, Kazumi Matsushige, Hirofumi Yamada

Bibliographic record

VenueApplied Physics Letters · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsMcGill University
Fundersnot available
KeywordsCantileverDissipationDissipative systemMicaNanometreMaterials scienceNon-contact atomic force microscopySurface forces apparatusFrequency modulationConductive atomic force microscopyOpticsAtomic force acoustic microscopyMechanicsAtomic force microscopyNanotechnologyPhysicsThermodynamicsMagnetic force microscopeComposite material

Abstract

fetched live from OpenAlex

Much interest has recently focused on the viscosity of nano-confined liquids. Frequency modulation atomic force microscopy (FM-AFM) is a powerful technique that can detect variations in the conservative and dissipative forces between a nanometer-scale tip and a sample surface. We now present an accurate formula to convert the dissipation power of the cantilever measured during the experiment to damping of the tip-sample system. We demonstrated the conversion of the dissipation power versus tip-sample separation curve measured using a colloidal probe cantilever on a mica surface in water to the damping curve, which showed a good agreement with the theoretical curve. Moreover, we obtained the damping curve from the dissipation power curve measured on the hydration layers on the mica surface using a nanometer-scale tip, demonstrating that the formula allows us to quantitatively measure the viscosity of a nano-confined liquid using FM-AFM.

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: none
Teacher disagreement score0.498
Threshold uncertainty score0.856

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 head0.011
GPT teacher head0.288
Teacher spread0.277 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueApplied Physics LettersSame topicForce Microscopy Techniques and ApplicationsFrench-language works237,207