Optimization of fs-laser-induced voxels in nonlinear materials via over-correction of spherical aberration
Bibliographic record
Abstract
In this Letter, over-correction of spherical aberration is used to counteract nonlinear effects such as Kerr self-focusing and plasma effects, resulting in more spherical and small-sized femtosecond laser-inscribed voxels within nonlinear materials. By strategically redirecting marginal focusing rays toward the beginning of the laser modification zone, the induced plasma prevents any rays from causing a structural modification beyond this zone, irrespective of any focus elongation caused by nonlinear effects. The method has been effectively validated across a range of materials, including ZnS, ZnSe, BIG, GeS4, and SiO2. A significant outcome is the achievement of quasi-spherical and (sub-)micrometer voxels in highly nonlinear materials. These findings open avenues for single-mode active waveguides and high-resolution patterning within nonlinear materials. The experiments are performed using a microscope objective equipped with a correction collar, a widely available tool in laboratories, highlighting the potential and versatility of the technique.
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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".