Gradient Refractive Index (GRIN) Optics: Monolithic Chalcogenide Optical Nanocomposites Enable Infrared System Innovation: Gradient Refractive Index Optics (Advanced Optical Materials 10/2020)
Bibliographic record
Abstract
This cover picture, referring to article number 2000150 by Myungkoo Kang, Kathleen A. Richardson and co-workers, illustrates that multi-component Ge–As–Pb–Se chalcogenide glasses are capable of forming transparent optical glass ceramic nanocomposites with the potential for use as infrared gradient refractive index optical components. Through a simple gradient heat treatment protocol, the glass system is converted to a nanocomposite where the spatially varying volume fraction of nucleated nanocrystals defines the resulting nanocomposite's effective optical properties. This modification results in systematic variations in refractive index and Abbe number of the transmissive nanocomposites. These data are critical in that they provide the design input data required to engineer arbitrarily-shaped, single-component gradient refractive index lenses with minimum spectral aberration. (Cover illustration: courtesy of Mia Truman.)
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".