Tunable 3D Plasmonic Cavity Nanosensors for Surface-Enhanced Raman Spectroscopy with Sub-femtomolar Limit of Detection
Bibliographic record
Abstract
Metallic nanohole arrays (NHAs) with a high hole density have emerged with potential applications for surface-enhanced Raman spectroscopy (SERS) including the detection of analytes at ultralow concentrations. However, these NHA structures generally yield weak localized surface plasmon resonance (LSPR), which is a prerequisite for SERS measurements. In this work, a compact three-dimensional (3D) tunable plasmonic cavity with extraordinary optical transmission properties serves as a molecular sensor with sub-femtomolar detection. The 3D nanosensor consists of a gold film containing an NHA with an underlying cavity and a gold nanocone array at the bottom of the cavity. These nanosensors provide remarkable surface plasmon polariton (SPP) and LSPR coupling, resulting in a significantly improved detection performance. The plasmonic tunability is evaluated both experimentally and theoretically. A SERS limit of detection of 10 –16 M for 4-nitrothiophenol is obtained along with distribution mapping of the molecule on the 3D plasmonic nanosensor. This results in an improved SERS enhancement factor of 10 7 obtained from a femtoliter plasmonic cavity volume. The tunability of these sensors can give rise to a potential opportunity for use in optical trapping while providing SERS sensing of a molecule of interest.
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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) | 0.000 | 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".