Plasmonic Nanorice Antenna on Triangle Nanoarray for Surface-Enhanced Raman Scattering Detection of Hepatitis B Virus DNA
Bibliographic record
Abstract
The sensitivity and the limit of detection of Raman sensors are limited by the extremely small scattering cross section of Raman labels. Silver nanorice antennae are coupled with a patterned gold triangle nanoarray chip to create spatially broadened plasmonic "hot spots", which enables a large density of Raman labels to experience strong local electromagnetic field. Finite difference time domain simulations have confirmed that the quasi-periodic structure increases the intensity and the area of the surface plasmon resonance (SPR), which enhances the surface-enhanced Raman scattering (SERS) signal significantly. The SERS signal of the nanorice/DNA/nanoarray chip is compared with that of the nanorice/DNA/film chip. The SERS signal is greatly enhanced when the Ag nanorices are coupled to the periodic Au nanoarray instead of the planar film chip. The resulting spatially broadened SPR field enables the SERS biosensor with a limit of detection of 50 aM toward hepatitis B virus DNA with the capability of discriminating a single-base mutant of DNA. This sensing platform can be extended to detect other chemical species and biomolecules such as proteins and small molecules.
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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".