Refractometric Sensing Using High-Order Diffraction Spots From Ordered Vertical Silicon Nanowire Arrays
Bibliographic record
Abstract
We propose to use high-order diffraction spots from 2-D silicon nanowire (NW) arrays for refractive index sensing based on spatial changes in the diffractive spots position. The NW arrays act both as a refractive index sensor and as dispersive elements, eliminating the need for external spectrometers for the measurement of refractive index changes. The setup uses a simple laser diode source and a low-cost camera and results in higher sensitivity to environmental refractive index changes, as compared with previously demonstrated colorimetric sensors. The sensitivity is greater for higher order diffraction spots, as compared with the lower order ones due to a larger dispersion angle change at higher orders. We also demonstrate that the observed diffraction angle and efficiency of the diffractive orders depend on a number of factors, such as excitation wavelength, NW diameters, pitch, and surrounding medium index. The simple solution of using diffraction spot displacements on a 2-D detector array would provide a novel means of sensing refractive index changes in the surrounding medium of NWs without the burden of complicated spectral analysis.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".