Ultrafast laser induced periodic sub-wavelength aluminum surface structures and nanoparticles in air and liquids
Bibliographic record
Abstract
In this communication, we demonstrate the generation of laser-induced periodic sub-wavelength surface structures (LIPSS) or ripples on a bulk aluminum (Al) and Al nanoparticles (NPs) by femtosecond (fs) laser direct writing technique. Laser irradiation was performed on Al surface at normal incidence in air and by immersing in ethanol (C2H5OH) and water (H2O) using linearly polarized Ti:sapphire fs laser pulses of ∼110 fs pulse duration and ∼800 nm wavelength. Field emission scanning electron microscope is utilized for imaging surface morphology of laser written structures and it reveals that the spatial periodicity as well as the surface morphology of the LIPSS depends on the surrounding dielectric medium and also on the various laser irradiation parameters. The observed LIPSS have been classified as low spatial frequency LIPSS which are perpendicularly oriented to the laser polarization with a periodicity from 460 to 620 nm and high spatial frequency LIPSS which spectacles a periodicity less than 100 nm with the orientation parallel to the polarization of the incident laser beam. Fabricated colloidal solutions, which contain the Al NPs, were characterized by UV-Vis absorption spectroscopy and transmission electron microscopy (TEM). TEM results reveal the formation of internal cavities in Al NPs both in ethanol and water. Formation mechanism of LIPSS and cavities inside the nanoparticles are discussed in detail.
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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".