Multiple scattering in resonant emulsions: Coherent-ballistic propagation and diffusive transport
Bibliographic record
Abstract
Ultrasonic pulse propagation experiments are reported on dilute suspensions of fluorinated-oil droplets immersed in a water-based gel matrix. These resonant emulsions are model systems for studying the effects of scattering resonances on wave transport since the large sound-speed contrast between the scatterers and the surrounding medium enhances the Mie resonances of the liquid particles. Measurements of the coherent-ballistic component reveal that both the scattering mean free path and the group velocity strongly depend on the frequency as predicted by the Independent Scattering Approximation. Scattering resonances are also responsible for very slow diffusivity of the multiply scattered ultrasound. This slowing down of the diffusion process due to resonances is well captured by models that include additional scattering delays of the ultrasonic pulses. The relationship between the diffusion coefficient and the ballistic data allow the frequency dependence of energy velocity of diffusing waves to be estimated, and show that the energy and group velocities are very different in our system. Although our ultrasonic measurements and their interpretation give a complete picture of wave transport in dilute resonant emulsions, the description of the wave transport in concentrated emulsions requires more sophisticated models based on the spectral function approach and the self-consistent theory.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".