Unconventional Polarization-Dependent Lasing Behavior in Birefringent CsPbBr <sub>3</sub> Hybrid Mode Plasmonic Nanolasers
Bibliographic record
Abstract
Semiconductor nanowires are sensitive to the polarization of light due to their one-dimensional structure and high dielectric contrast to the surrounding medium. This phenomenon enables configurations of polarization-sensitive nanoscale devices that can be potentially integrated onto a chip. Here, we demonstrate a hybrid plasmonic perovskite nanolaser that exhibits unconventional polarization dependence. Typical plasmonic nanolaser designs utilize a metallic substrate and a low-index buffer layer material. In this study, we use a birefringent CsPbBr 3 perovskite nanowire on a metal substrate separated by a thin Ta 2 O 5 buffer layer, exhibiting a refractive index lower than that along the ordinary axes of the nanowire, but higher than that along the extraordinary axes. In these conditions, we experimentally show a lower lasing threshold when the incident field is orthogonally polarized, i.e., along the b -axis. This is due to stronger electric field confinement at the nanowire–buffer interface as shown in simulation when pumped by orthogonal polarized light. This polarization sensitivity is unique to the hybrid plasmonic configuration and is not observed in the photonic counterpart, such as a nanowire on a quartz substrate. Furthermore, we found that short plasmonic nanowires exhibit lower lasing thresholds in addition to a larger polarization dependence, contrary to longer plasmonic nanowires. Moreover, orthogonally polarized pumping induces a larger-emission blueshift than longitudinally polarized pumping, attributed to strong exciton–polariton interactions. This blueshift is pronounced in plasmonic nanowires with lower lasing thresholds. This polarization-sensitive plasmonic nanolaser with reduced lasing threshold has potential applications in nanophotonic integrated circuits and room-temperature perovskite polaritonics.
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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".