Upconversion nanocrystal emission rate enhancement using double nanoholes
Bibliographic record
Abstract
Here we use optical trapping to isolate single Yb/Er-doped upconversion nanocrystals in plasmonic double nanohole apertures and show that the geometry of the aperture can be tuned to give high emission rate en- hancement. The double nanohole apertures show additional enhancement over the rectangular apertures that were previously demonstrated by our group, producing enough enhancement to observe emission at 400 nm and 1550 nm with 980 nm excitation—not seen in our group’s previous work with rectangular apertures. A facile method for tuning the geometry of double nanohole apertures by adjusting the plasma etching time in the colloidal lithography fabrication process is discussed. We find that a double nanohole with a cusp separation of 32 nm yields the greatest emission enhancement with multiple plasmonic resonances which enhance both the excitation and emission wavelengths. The emission enhancement for the DNH with 32 nm cusp separation was found to be a factor of 54, 44, and 31 greater than the rectangular apertures used in our group’s previous work, for wavelengths of 650 nm, 550 nm, and 400 nm. This result shows that double nanohole apertures can be tuned for emission enhancement as required by specific applications.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".