Hexoctahedron in a Nanoframe: Tailoring Stationary and Open Nanogaps for Single-Particle Surface-Enhanced Raman Scattering
Bibliographic record
Abstract
Plasmonic nanostructures with sharp features and nanogaps have been of immense interest in surface-enhanced Raman scattering (SERS) applications due to their strong hot spots generated at such morphological features. Here, we report a synthetic route to produce Au hexoctahedron-in-a-nanoframe structures (Au HIAFs), in which the high-curvature vertices of the Au hexoctahedral nanocrystal core fit tightly into the frame corners without the aid of an anchoring linker, realizing stationary, open nanogaps at sharp features within a single nanostructure. The prepared Au HIAFs can effectively exploit both sharp feature- and gap-enhanced electromagnetic fields, thereby exhibiting prominent SERS performance at the single-particle level. Due to the finely controlled, linker-free nanogaps of the Au HIAFs, the SERS detection of a series of analyte molecules could also be possible with an identical single Au HIAF through the reversible adsorption and desorption of analytes, highlighting their potential as a practical, reusable substrate for SERS-related applications.
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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".