Nanoplasmonic photonic crystal diatoms and phytoliths
Bibliographic record
Abstract
Evidence is emerging that silica-containing plant cells (phytoliths) and single cell micro-organisms (diatoms) exhibit optical properties reminiscent of photonic crystals. In the latter biosilicates, these properties appear to arise from light interactions with the intricate periodic patterns of micro- and nano-pores called foramina that are distributed over the frustule (outer silica shell). In this report, we show that Nitzschia Closterium pennate diatom frustules can be used to template arrays of nanoplasmonic particles to confer more complex physical properties, as shown by simulation and experiment. Selective templating of silver and gold nanoparticles in and around the array of pores was achieved by topochemical functionalization with nanoparticles deposited from solution, or by differential wetting/dewetting of evaporated gold films. The nanoplasmonic diatom frustules exhibit surface enhanced Raman scattering from chemisorbed 4-aminothiophenol. Thermally induced dewetting of gold films deposited on a frustule produces two classes of faceted gold nanoparticles. Larger particles of irregular shape are distributed with some degree of uniaxial anisotropy on the surface of the frustule. Smaller particles of more uniform size are deposited in a periodic manner in the frustule pores. It is thought that surface curvature and defects drive the hydrodynamic dewetting events that give rise to the different classes of nanoparticles. Finite difference time domain calculations on an idealized nanoplasmonic frustule suggest a complex electromagnetic field response due to coupling between localized surface plasmon modes of the nanoparticles in the foramina and an overlayer gold film.
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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".