Optical trapping of NaYF4:Er3+,Yb3+ upconverting fluorescent nanoparticles
Bibliographic record
Abstract
We report on the first experimental observation of stable optical trapping of dielectric NaYF4:Er(3+),Yb(3+) upconverting fluorescent nanoparticles (~26 nm in diameter) using a continuous wave 980 nm single-beam laser. The laser serves both to optically trap and to excite visible luminescence from the nanoparticles. Sequential loading of individual nanoparticles into the trap is observed from the analysis of the emitted luminescence. We demonstrate that the trapping strength and the number of individual nanoparticles trapped are dictated by both the laser power and nanoparticle density. The possible contribution of thermal effects has been investigated by performing trapping experiment in both heavy water and into distilled water. For the case of heavy water, thermal gradients are negligible and optical forces dominate the trap loading behaviour. The results provide a promising path towards real three dimensional manipulation of single NaYF4:Er(3+),Yb(3+) nanoparticles for precise fluorescence sensing in biophotonics experiments.
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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".