Coupling Perovskite Quantum Dot Pairs in Solution using a Nanoplasmonic Assembly
Bibliographic record
Abstract
Perovskite quantum dots (PQDs) provide a robust solution-based approach to efficient solar cells, bright light emitting devices, and quantum sources of light. Quantifying heterogeneity and understanding coupling between dots is critical for these applications. We use double-nanohole optical trapping to size individual dots and correlate to emission energy shifts from quantum confinement. We were able to assemble a second dot in the trap, which allows us to observe the coupling between dots. We observe a systematic red-shift of 1.1 ± 0.6 meV in the emission wavelength. Theoretical analysis shows that the observed shift is consistent with resonant energy transfer and is unusually large due to moderate-to-large quantum confinement in PQDs. This demonstrates the promise of PQDs for entanglement in quantum information applications. This work enables future in situ control of PQD growth as well as studies of the coupling between small PQD assemblies with quantum information applications in mind.
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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".