Spontaneous emission in nanofibers doped with an ensemble of quantum dots and quantum emitters
Bibliographic record
Abstract
We studied the effect of the spontaneous emission on the photoluminescence (PL) of photonic nanofibers doped with an ensemble of quantum dots (QDs) and quantum emitters. Quantum emitters can be molecular dyes or DNA molecules. Bound photonic states of the nanofiber hybrid are calculated using the transfer-matrix method based on the Maxwell equations. It is shown that the number of bound states in the nanofiber hybrid depends on the size and shape of the nanofiber along with the concentration of quantum dots and quantum emitters including their dielectric constants. The bound photon electric field induces dipoles in quantum dots and quantum emitters, and they interact with each other via the dipole-dipole interaction (DDI). We found that excited excitons decay spontaneously due to the interaction between excitons and the DDI field. It is found that the decay linewidth is enhanced when the bound photon energy is close to the exciton energy. On the other hand, we predicted that in the weak DDI coupling limit and when the bound photon energy is far away from the exciton energy the decay linewidths are suppressed (quenched). An analytical expression of the photoluminescence is found using the density-matrix method in the presence of the DDI coupling. We have predicted that in the strong DDI coupling limit the peak in the photoluminescence spectrum splits into two peaks when the bound photon energy is far away from the exciton energy. Furthermore, we have shown that when the bound photon energy is close to the exciton energy, two peaks merge into one peak. We have also compared our theory with PL experiments of a nanofiber doped with an ensemble of the CdSe QDs and sulforhodamine 101 dye molecules. A good agreement between theory and experiments is found. Our theory can be used by experimentalists to perform alternative types of experiments and for fabricating types of nanosensors and nanoswitches.
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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 | 0.000 |
| 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".