Electrically modulated near-field energy transfer between quantum dots and perovskite nanocrystals
Bibliographic record
Abstract
Electrically controlling resonance energy transfer of optical emitters provides a novel mechanism to switch nanoscale light sources on and off individually for optoelectronic applications. Cesium lead halide nanocrystals have emerged as a candidate for optoelectronic applications, seamlessly blending the favorable advantages of perovskites and quantum dots. Here, we demonstrate nonradiative energy transfer between CsPbBr 3 nanocrystals and colloidal quantum dots in a heterostructure device. We fabricate devices with semiconducting, chemically synthesised cesium lead bromide (CsPbBr 3 ) perovskite nanocrystals (PerNCs) as an electrostatically gated donor and core–shell quantum dots (QDs) as an acceptor. With the help of a bottom-gate electrode and hafnium oxide (HfO 2 ) dielectric layer, the Förster resonance energy transfer (FRET) efficiency can be modulated. Thicknesses of the dielectric, donor, and acceptor layers were fine-tuned and the optimized device configuration exhibits up to 80% modulation of photoluminescence intensity, making it suitable for potential applications in optoelectronic devices and energy conversion.
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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) | 0.001 | 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".