Particle Motion in a Macroscale, Multiwavelength Acoustic Field
Bibliographic record
Abstract
Particle motion due to ultrasonic acoustic radiation in a macroscale, multiwavelength acoustic chamber is investigated and compared with available theories. Primary acoustic radiation force theory has been extensively developed to predict single particle motion in a microscale, single-node acoustic chamber/channel. There is a need to investigate the applicability of this theory to macroscale, multiwavelength acoustic channels utilizing the acoustic radiation force for separating polydispersed particles. A particle-tracking velocimetry (PTV) approach for measuring individual particle motion is developed specifically to track particles as they densify at an acoustic pressure node. Particle motion is tracked over the lifetime of their motion to a node. Good agreement between the experimental and theoretical results is observed in the early stages of particle motion, where particles can be considered individually. Only in the densified region of the acoustic pressure node is there some mismatch with theory. The acoustic energy density of the acoustic chamber, a parameter intrinsically associated with the system by the theory, is also determined experimentally for different conditions and shown to be constant for all investigated system settings. The investigation demonstrates the capability of available theory in predicting the motion of polydispersed particles in macroscale, multiwavelength acoustic chambers.
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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".