Multiscale Visualization of Colloidal Particle Lens Array Mediated Plasma Dynamics for Dielectric Nanoparticle Enhanced Femtosecond Laser-Induced Breakdown Spectroscopy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.001 |
| 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 it