F 2 -laser microwelding of optical fibers and glass substrates
Bibliographic record
Abstract
Laser welding of optical glasses remains a challenging area today because of the weak optical absorption typically available with most commercial lasers and the brittle nature of glass. In this paper, we demonstrate for the first time to our best knowledge, the laser welding of telecommunication optical fiber onto a fused silica substrate. The 157-nm F<sub>2</sub> laser was selected for the wide processing window that drives strong absorption at high fluence exposure > 1 J/cm<sup>2</sup> without inducing microcrack formation. The method of second surface ablation was applied to the contact point between the glass plate and glass fiber to locally heat, melt, and reflow the glass and thereby weld together the two similar glasses. Mechanical pressure was applied while the laser beam was scanned along the sample contact to produce a line of overlapping welds of 25-um spot size each. Fused silica samples of up to several hundreds of microns thick could be welded owing to a large 157-nm penetration depth of 1/a ≈ 1 mm. A narrow 3.31 to 3.66 J/cm<sup>2</sup> fluence window was found for laser welding through 160-um thick fused silica substrates. The F<sub>2</sub>-laser welding window is constrained by the need for sufficient transmitted fluence to melt the interface without too much fluence that will damaged the interface structure at the onset of ablation or induce front surface ablation.
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.
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 | 0.001 | 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".