Stoichiometric Engineering of Chalcogenide Semiconductor Alloys for Nanophotonic Applications
Bibliographic record
Abstract
A variety of alternative plasmonic and dielectric material platforms-among them nitrides, semiconductors, and conductive oxides-have come to prominence in recent years as means to address the shortcomings of noble metals (including Joule losses, cost, and passive character) in certain nanophotonic and optical-frequency metamaterial applications. Here, it is shown that chalcogenide semiconductor alloys offer a uniquely broad pallet of optical properties, complementary to those of existing material platforms, which can be controlled by stoichiometric design. Using combinatorial high-throughput techniques, the extraordinary epsilon-near-zero, plasmonic, and low/high-index characteristics of Bi:Sb:Te alloys are explored. Depending upon composition they can, for example, have plasmonic figures of merit higher than conductive oxides and nitrides across the entire UV-NIR range, and higher than gold below 550 nm; present dielectric figures of merit better than conductive oxides at near-infrared telecommunications wavelengths; and exhibit record-breaking refractive indices as low as 0.7 and as high as 11.5.
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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) | 0.001 | 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 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".