Roadmap on chalcogenide photonics
Bibliographic record
Abstract
Abstract Alloys of sulfur, selenium and tellurium, often referred to as chalcogenide semiconductors, offer a highly versatile, compositionally-controllable material platform for a variety of passive and active photonic applications. They are optically nonlinear, photoconductive materials with wide transmission windows that present various high- and low-index dielectric, low-epsilon and plasmonic properties across ultra-violet, visible and infrared frequencies, in addition to an, non-volatile, electrically/optically induced switching capability between phase states with markedly different electromagnetic properties. This roadmap collection presents an in-depth account of the critical role that chalcogenide semiconductors play within various traditional and emerging photonic technology platforms. The potential of this field going forward is demonstrated by presenting context and outlook on selected socio-economically important research streams utilizing chalcogenide semiconductors. To this end, this roadmap encompasses selected topics that range from systematic design of material properties and switching kinetics to device-level nanostructuring and integration within various photonic system architectures.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.010 |
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".