Distance Dependence of Förster Resonance Energy Transfer Rates in 2D Perovskite Quantum Wells via Control of Organic Spacer Length
Bibliographic record
Abstract
Two-dimensional (2D) semiconductors are attractive candidates for a variety of optoelectronic applications owing to the unique electronic properties that arise from quantum confinement along a single dimension. Incorporating nonradiative mechanisms that enable directed migration of bound charge carriers, such as Förster resonance energy transfer (FRET), could boost device efficiencies provided that FRET rates outpace undesired relaxation pathways. However, predictive models for FRET between distinct 2D states are lacking, particularly with respect to the distance d between a donor and acceptor. We approach FRET in systems with binary mixtures of donor and acceptor 2D perovskite quantum wells (PQWs), and we synthetically tune distances between donor and acceptor by varying alkylammonium spacer cation lengths. FRET rates are monitored using transient absorption spectroscopy and ultrafast photoluminescence, revealing rapid picosecond lifetimes that scale with spacer cation length. We theoretically model these binary mixtures of PQWs, describing the emitters as classical oscillating dipoles. We find agreement with our empirical lifetimes and then determine the effects of lateral extent and layer thickness, establishing fundamental principles for FRET in 2D materials.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".