Tunable nanolaser based on quasi-BIC in a slanted resonant waveguide grating
Bibliographic record
Abstract
Nanolasers based on quasi-bound states in the continuum (quasi-BIC) have attracted much attention owing to its unique optical properties providing strong light–matter interaction. Although various quasi-BIC lasers have been designed, so far, few efforts have been devoted to their tunability in wavelength. Here we propose an approach to employ quasi-BIC and guided mode in a slanted resonant waveguide grating. The proposed structure supports a specially designed eigenmode localized both in the grating and in the DAST layer, which allows to obtain lasing emission and meanwhile the ability to tune the wavelength via electro-optic effect. Numerical simulation results show that the threshold is approximately 7.75 μJ / cm2 with the tuning range being 28 nm. In addition, we show that the distribution of the lasing intensity between the transmission and reflection directions can be controlled by changing the parameters of the structure. This work shows good potential of combining quasi-BIC with guided mode to design tunable nanolaser.
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 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".