Engineering Directionality in Quantum Dot Shell Lasing Using Plasmonic Lattices
Bibliographic record
Abstract
We report how the direction of quantum dot (QD) lasing can be engineered by exploiting high-symmetry points in plasmonic nanoparticle (NP) lattices. The nanolaser architecture consists of CdSe-CdS core-shell QD layers conformally coated on two-dimensional square arrays of Ag NPs. Using waveguide-surface lattice resonances (W-SLRs) near the Δ point in the Brillouin zone as optical feedback, we achieved lasing from the gain in CdS shells at off-normal emission angles. Changing the periodicity of the plasmonic lattices enables other high-symmetry points (Γ or M) of the lattice to overlap with the QD shell emission, which facilitates tuning of the lasing direction. We also increased the thickness of the QD layer to introduce higher-order W-SLR modes with additional avoided crossings in the band structure, which expands the selection of cavity modes for any desired lasing emission angle.
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 | 0.000 |
| 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 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".