Multiscale Visualization of Colloidal Particle Lens Array Mediated Plasma Dynamics for Dielectric Nanoparticle Enhanced Femtosecond Laser-Induced Breakdown Spectroscopy
Bibliographic record
Abstract
A multiscale visualization of silica colloidal particle lens array (CPLA) assisted laser ablation of copper is investigated. The distributed holes on a crater of CPLA-deposited Cu (CPLA-Cu) show a near-field effect by the silica nanoparticles (NPs), and the plasma emission signal of CPLA-Cu is 3-5 times as strong as that of Cu. Time-resolved plasma expansion, shockwave propagation, plasma plume emission, and nanoparticle distribution are observed and analyzed for ablations on both Cu and CPLA-Cu substrates. The initial expansion of plasma generated on CPLA-Cu is faster than that of pristine Cu. The shockwave of CPLA-Cu is rounder and its plasma plume is wider than those of Cu. The nanoparticle distribution shows a strong lateral collision during plume ejection for CPLA-Cu. Plasma characterization shows the increased plasma temperature is the key reason for femtosecond laser-induced breakdown spectroscopy (fs-LIBS) signal enhancement. This work demonstrates the signal enhancement effect of dielectric NPs on fs-LIBS and provides insights into hydrodynamics of the fs laser-induced plasma generated on CPLA-deposited substrate.
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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".