Bibliographic record
Abstract
Investigations are being carried out to improve the quality of laser micromachining of glass and semiconductor materials and to achieve submicron finished tolerances. Experiments have been carried out mainly with wavelengths ranging from 248 to 800 nm and pulse lengths of 130 to 400 fs. Comparisons are also being made with machining using 10 ns excimer laser pulses. Laser ablation thresholds, incubation coefficients and ablation rates are measured using single and multiple shot irradiation over a range of incident fluences with well controlled gaussian beams. New techniques for debris removal and crack minimization are being investigated. One technique for debris removal uses a sacrificial thin film of sputtered tungsten on top of the substrate before micromachining. After ablation, the tungsten film and deposited debris may be etched away with hydrogen peroxide. This technique has shown promising results in leaving a much cleaner surface. In order to reduce the amount of cracking of the substrate during laser drilling of glass, we have also been investigating the use of preheated substrates. By raising the temperature of glass before drilling, the sample is more ductile and less prone to cracking.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".