Ultrasonic investigation of phonon localization in a disordered three-dimensional "mesoglass"
Bibliographic record
Abstract
One of the long standing questions in phonon physics has been whether or not the Anderson localization of acoustic phonons can be demonstrated unambiguously in disordered materials. In this paper, this question is addressed by reporting signatures of the localization of ultrasonic waves in a "mesoglass" made from a disordered three-dimensional network of aluminum beads. In the upper part of the intermediate frequency regime, which extends over the range of frequencies where the acoustic phonon wavelength is comparable with the sizes of the pores and beads, the intensity distributions of the speckle patterns due to strong multiple scattering show clear departures from Rayleigh statistics, with a variance that increases with frequency. This intensity distribution can be fitted with a stretched exponential, consistent with recent predictions for localization. In this frequency range, the time-of-flight profile of the transmitted intensity exhibits a non-exponential decay, which may be construed as a slowing down of the phonon diffusion coefficient with propagation time. These results are interpreted using recent theoretical predictions based on the self-consistent theory of the dynamics of localization, showing that our experimental data are consistent with the localization of acoustic waves in this mesoglass, and further elucidating their behaviour.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".