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
Abstract The nonlinear optical response of materials allows optical functionality not seen in linear devices, such as switching, wavelength conversion, and adaptive optics. Unfortunately, the nonlinear optical response is weak in naturally occurring materials, making many ultrafast information processing applications impractical from an efficiency point of view. Nonlinear plasmonic metasurfaces, as a subset of metamaterials, aim to provide a more efficient and functional nonlinear optical response by tailoring the configuration of nanostructures. Metasurfaces are compact, cascadable, and easy to fabricate with established planar technologies, and therefore deserve particular attention. In this review, advances in nonlinear plasmonic metasurfaces are presented, including theoretical approaches, design methodologies, and key demonstrations of functionality. The theoretical approach first considers the linear response of the plasmonic metal and then uses this to calculate the nonlinear scattering. Design methodologies are considered including limits on gap size enhancements, tunneling and charging effects, and thermal management. Key demonstrations such as efficiency in wavelength conversion, functional wavelength conversion, and switching are also reviewed. Finally, an outlook on the future development in this field of research is offered, aiming at efficient and ultrafast optical information processing.
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) | 0.001 | 0.002 |
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