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, GeS 4 , and SiO 2 . 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.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".