Phase‐Locked Lasing in 1D and 2D Patterned Metal–Organic Microcavities
Bibliographic record
Abstract
Abstract Organic microcavities provide unique properties that are highly advantageous for designing microlasers, but lack in efficient ways to directly integrate electrodes able to drive high currents. The introduction of thin, patterned metal films, leading to the formation of local Tamm plasmon polariton states, has been recently demonstrated as a possible route to preserving coherence in the presence of significant optical loss. Here, periodic micron‐scale gratings of silver are embedded into a high‐quality organic microcavity, creating a crystal‐like photonic potential structure. Despite strong absorption of metallic layers, these structures readily lase upon optical excitation. In that case, the above threshold emission originates not from isolate metal‐free areas but instead from phase‐locked supermodes spreading over several grating periods. Remarkably, in‐plane coherence can spread even further when decreasing the grating period, covering distances of more than 50 m and more than ten metal stripes. 1D and 2D gratings with varying periods are investigated using tomographic scanning of the k‐space emission fine structure, which exhibits a strong dependence on the grating geometry. These results support the fabrication of highly customizable organic microlasers with tailored in‐plane coherence, and demonstrate the coexistence of extended coherence and optical loss.
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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) | 0.000 | 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 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".