Laser-induced incandescence of iron nanoparticles: effects of laser-induced sintering and coalescence
Bibliographic record
Abstract
While time-resolved laser-induced incandescence is a promising technique for characterizing metal nanoparticles in the gas phase, there remain several commonly observed and unexplained features in the data, including larger-than-predicted absorption cross-sections (excessive absorption) and faster-than-predicted cooling rates immediately following peak emission (apparent anomalous cooling). In the case of low melting point metals such as iron, laser-heated aggregates coalesce into spheres (i.e., fully sinter) before the peak of the LII signal is reached. Coalescence may affect the observed TiRe-LII signals in two ways: (i) the transition from aggregates to spheres reduces the absorption cross-section, which affects both the total absorbed laser energy and the intensity of the emitted incandescence in a wavelength-dependent manner; and (ii) surface energy is converted into sensible energy of the nanoparticles, which increases their peak temperature. While the revised LII model does not completely account for the rapid signal decay immediately following the peak signal, the predicted curves align more closely with the measured intensities from coalesced particles during the later cooling times. Supplementary Information: The online version contains supplementary material available at 10.1007/s00340-025-08504-0.
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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 | 0.000 |
| 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".