Multiscale models of plasmonic structural colors with nanoscale surface roughness
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Plasmonic coloration arises from resonant interaction between visible light and metallic nanostructures, which causes wavelength-selective absorption or scattering of light. This effect is sensitive to surface roughness that can perturb these resonant interactions and cause observed coloration to deviate from coloration predicted by simulations. We present a computational visualization approach that incorporates electrodynamic simulations and physically based rendering (PBR) to investigate the effect of nanoscale roughness on the structural coloration from thin, planar silver films decorated with nanohole arrays. Nanoscale roughness is modeled mathematically by a surface correlation function and parameterized in terms of roughness that is either out of or into the plane of the film. Our results provide photorealistic visualization of the influence of nanoscale roughness on the coloration from silver nanohole arrays in both reflectance and transmittance. Out-of-plane roughness has a significantly greater effect on coloration than in-plane roughness. The methodology introduced in this work is useful for modeling artificial coloration phenomena.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it