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Record W2060390435 · doi:10.1063/1.3012811

A new physical model for resonance shear measurement of confined liquids between solid surfaces

2008· article· en· W2060390435 on OpenAlexaff
Masashi Mizukami, Kazue Kurihara

Bibliographic record

VenueReview of Scientific Instruments · 2008
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsMaterials scienceResonance (particle physics)Shear (geology)RheologyViscosityMicrometerNanometreSurface forces apparatusMechanicsThermodynamicsOpticsNanotechnologyComposite materialPhysicsAtomic physics

Abstract

fetched live from OpenAlex

This paper describes a new physical model for resonance shear measurement. The resonance shear method developed by us provides a tool for investigating the rheological and tribological properties of liquids confined between two surfaces as a function of the surface distance from micrometer to zero (contact) with nanometer level resolution with high sensitivity and stability. The properties of the confined liquid can be quantitatively studied by analyzing the resonance curve using a physical model. However, the quantitative analysis using the previously developed model was applicable only for the condition of the relatively low liquid viscosity (below approximately 100 Pa s). A new physical model described in this paper enabled us to continuously analyze the properties of confined liquids at all distances, which was not possible by the previous model. It became possible to calculate the movement of a lower surface and the shear rate applied on the confined sample using the parameters obtained from the resonance curves.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.058
GPT teacher head0.273
Teacher spread0.216 · 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

Citations49
Published2008
Admission routes1
Has abstractyes

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