Cavitation Nuclei Regeneration in a Water-Particle Suspension
Bibliographic record
Abstract
Bubble nucleation in water induced by boiling, gas supersaturation, or cavitation usually originates from preexisting gas cavities trapped into solid defects. Even though the destabilization of such gas pockets, called nuclei, has been extensively studied, little is known on the nuclei dynamic. Here, nuclei of water-particle suspensions are excited by acoustic cavitation, and their dynamic is investigated by monitoring the cavitation probability over several thousand pulses. A stable and reproducible cavitation probability emerges after a few thousand pulses and depends on particle concentration, hydrophobicity, and dissolved gas content. Our observations indicate that a stable nuclei distribution is reached at a later time, different from previously reported nuclei depletion in early time. This apparent paradox is elucidated by varying the excitation rate, where the cavitation activity increases with the repetition period, indicating that the nuclei depletion is balanced by spontaneous nucleation or growth of nuclei. A model of this self-supporting generation of nuclei suggests an origin from dissolved gas adsorption on surfaces. The method developed can be utilized to further understand the spontaneous formation and distribution of nanosized bubbles on heterogeneous surfaces.
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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) | 0.001 | 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".