Spectroscopic monitoring of FeO fluorescence for laser treatment of steel surfaces in air
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
Laser treatment of steel surfaces in air using continuous-wave radiation emitted by a fiber laser at 1.07 μm is investigated using a spectroscopic method that monitors the presence of FeO molecular fluorescence. For all conditions tested, the irradiance levels remained below 106 W/cm2 thus inhibiting the formation of plasma. In this paper, we demonstrate that FeO emissions are related to laser-induced steel vaporization and can be used to monitor the performances of the laser system for drilling and cutting applications. The heated Fe atoms oxidize rapidly forming solid and liquid FeO at the interface with the oxygen-filled atmosphere. As the formation of FeO is exothermic and that the presence of the oxide further increases laser absorption, the laser-induced oxide is rapidly vaporized and ejected off the surface, leaving an empty hole. The presence of FeO molecules can be monitored via the characteristic fluorescence emitted from the well-known orange system which is excited by the treating of laser itself. Excellent quantitative agreement was found between the FeO signal strength and the volume of material ablated by the laser beam in a drilling configuration allowing real-time monitoring of the interaction for process optimization.
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 | 0.000 |
| 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 it