P2L-3 Effects of Sound Field and Acoustic Streaming on Nanometer Sized Diamond Particles Dispersion System using Ultrasound
Bibliographic record
Abstract
We reported the improvement of dispersion of nanometer sized diamond particles using shock wave and active oxygen species by acoustic cavitation at 155 kHz in 2004 IEEE International UFFC Joint 50th Anniversary Conference in Montreal. Average sound pressure calculated from sound pressure distribution in horizontal plane at distance of 10 mm from a stainless steel vibrating disk in water tank was used as acoustic index for improvement of dispersion of the diamond particles. The measured horizontal plane was on the loop of the standing wave acoustic field. However, improvement of dispersion characteristics of the particles was performed in whole water in the water tank. Therefore, each sound pressure distribution in horizontal plane at the distances of 10 mm to 95 mm from the stainless steel vibrating disk was measured by hydrophone. Sound pressure distribution all over water in the water tank was observed three dimensionally. The generation of active oxygen species in the water tank was estimated by observation of sonochemical luminescence. As the results, higher sound pressure than 100 kPa was measured in central region lower than height of 55 mm from the stainless steel vibrating disk in the water tank. Sonochemical luminescence could not be observed in above region in the water tank. They were contradictory results. We guess that the acoustic streaming prevents from trapping cavitation bubble at the loop of standing wave sound field. We think that the acoustic streaming is one cause of the contradictory results. Homogenous sound pressure distribution is required improvement of dispersion characteristics of nanometer sized diamond particles by ultrasound exposure
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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".