Investigation of femtosecond laser written waveguide refractive index change in toughened glass: Towards integration of photonics device inside cellphone screens (Conference Presentation)
Bibliographic record
Abstract
Femtosecond laser written devices inside a smartphone screen, in this case Gorilla Glass ®, have been recently demonstrated1 with a high potential of increasing the functionality of cellphones, consuming minimal space using the glass screen2. Even though low loss waveguides have been reported in this glass, the behavior of the refractive index of the glass subject to femtosecond laser radiation is not well understood. Here, we propose a study of that behavior by presenting the identification of two major transitions where the induced refractive index seems to decrease. The first transition occurs at lower fluence and is characterized by a single structure while the second one occurs at much higher fluences, and is well characterized by a double shell structure. In both these transitions, the refractive index at the center of the structure seems to decrease. However, it should be noted that between these two regimes, there is narrow regime in which light seem to be guide in the middle of the fs processed region, confirming the possibility of making a single pass waveguide. The fluence limits of each regime has been investigated as has the quality of the waveguide made by a single and multi-passes. The refractive index of the affected zones is mapped by a highly sensitive phase-interference technique. [1] Lapointe, J., Gagné, M., Li M.J., and Kashyap R., "Making smart phones smarter with photonics," Op. Exp., Vol. 22, No. 13, pp. 15473-15483, (2014) [2] Lapointe, J., Parent, F., Soares de Lima Filho, E., Loranger, S., and Kashyap R. "Toward the integration of optical sensors in smartphone screens using femtosecond laser writing," Optics Letters, Vol. 40, No. 23, pp. 5654-5657, (2015)
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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".