Optical Trapping of 12 nm Dielectric Spheres Using Double-Nanoholes in a Gold Film
Bibliographic record
Abstract
Optical tweezers have found many applications in biology, but for reasonable intensities, conventional traps are limited to particles >100 nm in size. We use a double-nanohole in a gold film to experimentally trap individual nanospheres, including 20 nm polystyrene spheres and 12 nm silica spheres, at a well-defined trapping point. We present statistical studies on the trapping time, showing an exponential dependence on the optical power. Trapping experiments are repeated for different particles and several nanoholes with different gap dimensions. Unusually, smaller particles can be more easily trapped than larger ones with the double-nanohole. The 12 nm silica sphere has a size and a refractive index comparable to the smallest virus particles and has a spherical shape which is the worst case scenario for trapping.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.138 | 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 teacher head, 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".