Collective and local energy transfer in biologically-hybridized systems of semiconductor quantum dots and metallic nanoantenna arrays
Bibliographic record
Abstract
Abstract We study polarization-dependent energy transfer and exciton dynamics in hybrid systems consisting of quantum dot bioconjugates and arrays of metallic nanoantennas. The size distribution of the quantum dots are used to investigate how excitons with different transition energies interact with the localized surface plasmon resonances (LSPRs) and collective surface lattice resonances (SLRs) supported by the arrays. We show that, depending on the projections of the electric dipoles of the quantum dots along the nanoantennas, they can interact with these resonances differently. This leads to polarization-dependent radiative and non-radiative decay of excitons, highlighting such systems can support two types of energy transfer mechanisms: (i) collective wavelength-dependent transfer of excitation energy from quantum dots to the arrays of the metallic nanoantennas via SLR (photonic-plasmonic path), and (ii) the local energy transfer to individual nanoantennas via localized surface plasmons (direct path). Our results also show that quantum dots with larger cores can have stronger interaction with SLRs. This suggests that such resonances can act as an energy drain that enhances cascaded energy transfer between quantum dots.
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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".