Optimizing Cu-alloy surface characteristics through magnetic field-enhanced fs laser treatment
Bibliographic record
Abstract
We report here the effect of the magnetic field on plasma parameters and the surface structuring of the Cu alloy after fs laser irradiation. A Ti:Sapphire (800 nm, 35 fs, 1 KHz) laser is employed at various irradiances (0.011–0.117 PW/cm2) to generate plasma. A Transvers Magnetic Field (TMF) of strength 1.1 T is employed for plasma confinement. All the measurements were performed with and without TMF. The Cu plasma parameters, i.e., excitation temperature (Texc) and electron number sensity (ne), determined by laser-induced breakdown spectroscopy analysis, are higher in the presence of TMF. This magnetic field confinement of Cu plasma was studied analytically by evaluating thermal beta (βt), directional beta (βd), confinement radius (Rb), and diffusion time (td). To correlate Cu-alloy plasma parameters with surface modifications, field emission scanning electron microscope analysis is performed. It reveals the formation of low-spatial-frequency laser-induced periodic surface structures (LIPSSs) and high-spatial-frequency LIPSSs, along with agglomers and nano-rims formation. Distinct and well-defined structures are observed in the presence of a magnetic field. It is concluded that controlled surface structuring can be achieved through magnetic confinement, which enhances key plasma parameters. The technique has the potential for enhancing the fabrication of nano-gratings and field emitters, where spatial uniformity is critically important.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".