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Record W1974474501 · doi:10.1121/1.3507980

Scaling of viscoelastic shell properties of lipid encapsulated microbubbles with frequency.

2010· article· en· W1974474501 on OpenAlexaff
Emma Huo, Brandon Helfield, David E. Goertz

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2010
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsViscoelasticityBubbleAttenuationElasticity (physics)Materials scienceMicrobubblesViscosityScalingMechanicsShell (structure)Rayleigh scatteringComposite materialAcousticsOpticsPhysicsUltrasoundMathematics

Abstract

fetched live from OpenAlex

While it has been established that nonlinear oscillations of lipid encapsulated microbubbles occur at frequencies of >10 MHz, the understanding of bubble behavior in this frequency range is limited and is not predicted by bubble models using shell properties derived at <5 MHz. Here we investigate the scaling of the viscoelastic shell properties of lipid encapsulated contrast agents with frequency and bubble size. Attenuation measurements were performed over 2–30 MHz and, using size distribution measurements and the linearized Rayleigh–Plesset equation, shell elasticity and viscosity terms were estimated. Experiments were performed on a series of narrow size distribution in-house agents with progressively smaller diameters, as well as the high frequency agent Micromarker. In-house agents peaked in attenuation at 4.2, 8.5, 13, and 22 MHz, and Micromarker rose until 21 MHz. The elasticity for in-house agents was comparable to other agents at lower frequencies, while the viscosity rapidly decreased above 10 MHz. For Micromarker, which has a different fabrication process, the elasticity was substantially higher than the in-house agent and over 15–30 MHz its viscosity was far lower viscosity than those reported at lower frequencies. The use of low shell viscosities in bubble models enables the prediction of nonlinear oscillations at higher frequencies.

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 score0.151
Threshold uncertainty score0.287

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 studies0.0000.001
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 head0.006
GPT teacher head0.183
Teacher spread0.177 · 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

Citations10
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicUltrasound and Hyperthermia ApplicationsFrench-language works237,207