Medical applications of hybrids made from quantum emitter and metallic nanoshell
Bibliographic record
Abstract
We have studied the photoluminescence emission in a quantum emitter and metallic nanoshell hybrid system. The metallic nanoshell is made of a dielectric core coated with a thin layer of metal and is surrounded by biological cells such as cancer cells. Surface plasmon polariton resonances in the metallic nanoshell are calculated using Maxwell's equations in the quasi-static approximation. It is found that the metallic nanoshell has two surface plasmon polariton resonances. Locations of surface plasmon polariton resonances can be manipulated by changing the size of the core and the metallic shell. We have compared our theory with the extinction coefficient of metallic nanoshells. A good agreement between theory and experiment is found. A probe laser field is applied to study the photoluminescence spectrum in the hybrid system. Dipoles are induced in the metallic nanoshell and quantum emitter due to the probe laser. Hence the quantum emitter and metallic nanoshell interact via the dipole-dipole interaction. The photoluminescence spectrum of the quantum emitter is calculated using the density matrix method in the presence of the dipole-dipole interaction. It is found that the photoluminescence spectrum of the quantum emitter with degenerate excitons splits from one peak to two or three peaks depending on the locations of two surface plasmon polariton resonances. Similarly, for the nondegenerate quantum emitter we found that the photoluminescence spectrum splits from two peaks to four peaks. These interesting findings may be useful in the fabrication of nanosensors, nanoswitches, and for other applications in medicine.
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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) | 0.000 | 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 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".