UV laser excited surface acoustic waves - quantitative measurements and comparison with theory
Bibliographic record
Abstract
Summary form only given. Laser excitation and detection of acoustic waves is a powerful tool for investigating material properties. In order for acoustics to be useful in industrial settings, large amplitude deflections of several nanometers are required to be clearly visible, above background noise. Previous studies using infrared Nd:YAG laser pulses have indicated that surface acoustic wave amplitudes of 2 nm peak to peak and 8 nm peak to peak can be excited at distances of 10 mm and 7 mm respectively with laser energies of 80 mJ and 30 mJ respectively. Thus there appears, to be differences in the measured wave amplitudes in the previous studies. We expect that UV laser pulses which suffer less plasma shielding from air breakdown and generate higher ablation pressures due to, coupling to higher plasma densities are capable of generating larger amplitude acoustic waves than infrared, laser pulses. A full study is being carried out of the ablative excitation, of surface acoustic waves in order to determine such parameters as magnitude and shape of the, acoustic wave and the velocity at which the wave, propagates. Few quantitative studies of the amplitude and shape of the surface acoustic wave have been reported to date and all of these have been for visible or infrared pulse excitation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".