Silicon quantum dot coated microspheres for microfluidic refractive index sensing
Bibliographic record
Abstract
The electromagnetic resonances of optical microspheres—the so-called whispering gallery modes (WGMs)—can be used for refractometric sensing of surrounding fluids. Microspheres are attractive because they offer high sensitivity and can be utilized with fluorescent dyes or quantum dots. One issue with microspheres, however, is that they are difficult to integrate into microfluidic systems. Here, we develop a microfluidic structure that permits sensing applications using a single microsphere in a capillary. To achieve this, a microsphere formed on the end of a tapered fiber was first coated with fluorescent silicon quantum dots (QDs). The sphere was then inserted into a microcapillary and the fluorescence WGMs were monitored as different fluids were pumped through the channel. The sensitivity and detection limits for this sphere-in-a-capillary device were measured for several different QD film thicknesses and for two different microsphere sizes. Because of the relatively high-visibility mode structure, the sensitivity and detection limit can be defined by Fourier analysis of the free spectral range and WGM spectral shifts.
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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) | 0.001 | 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".