Analytical and physical optimization of nanohole-array sensors prepared by modified nanosphere lithography
Bibliographic record
Abstract
The analytical and physical properties are reported for nanohole arrays prepared with glancing angle deposition (GLAD) or plasma treatment of a nanosphere lithography (NSL) mask prior to the deposition of a thin Au film. The nanohole arrays obtained with a 450 nm nanospheres mask are characterized using atomic force microscopy (AFM) to determine the depth and the width of the nanoholes, and the periodicity of the nanohole arrays. The analytical properties are reported in terms of the surface plasmon (SP) excitation wavelength (500 nm to 1000 nm), sensitivity to refractive index (27 nm RIU(-1) to 487 nm RIU(-1)), sensitivity to monolayer formation (shift of the SP band by approx. 1 nm), and refractive index resolution (10(-4) RIU). These simple techniques produce well-ordered nanohole arrays with tunable analytical and physical properties for the development of biosensors.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".