Burst train generator of high energy femtosecond laser pulses for driving heat accumulation effect during micromachining
Bibliographic record
Abstract
A new method for generating high-repetition-rate (12.7-38.2 MHz) burst trains of femtosecond laser pulses has been demonstrated for the purpose of tailoring ultrashort laser interactions in material processing that can harness the heat accumulation effect among pulses separated by a short interval (i.e., 26 ns). Computer-controlled time delays were applied to synchronously trigger the high frequency switching of a high voltage Pockels cell to specify distinctive values of polarization rotation for each round-trip of a laser pulse cycling within a passive resonator. Polarization dependent output coupling facilitated the flexible shaping of the burst envelope profile to provide burst trains of up to ∼1 mJ of burst energy divided over a selectable number (1 to 25) of pulses. Individual pulses of variable energy up to 150 μJ and with pulse duration tunable over 70 fs to 2 ps, were applied in burst trains to generate deep and high aspect ratio holes that could not form with low-repetition-rate laser pulses.
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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".