Transmission enhancement in chalco-halide glasses for multiband applications
Bibliographic record
Abstract
The potential of clear Ga2S3-GeS2-CsCl based sulfide glasses transparent up to 11.5 μm to be used as new optical material for multispectral applications has been investigated. The addition of large amount of chlorine ions – above 40 mol.% of CsCl – into the chalcogenide vitreous network in order to produce colorless glasses results in a drastic increase of their water contamination. We report for the first time, to the best of our knowledge, the purification of cesium chloride CsCl by dynamic distillations under vacuum in order to reduce water and hydroxyl group contamination before complete melting of the glass. Besides, sulfur purification by dynamic and static distillations was also performed in the implemented method. The obtained glasses were then characterized by UV-visible and infrared (FTIR) spectroscopies, by electron probe microanalysis (EPMA), thermal analysis (DSC), and their refractive indices in the visible and near infrared ranges were also measured. A large improvement of the glass transmission spectrum has been achieved with an estimated reduction of about 45 times of the OH and H2O content and 60 times of the SH content. The glass thermal molding ability and chemical durability with and without protective coating have been tested to probe their potential for fabrication of complex optics.
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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 | 0.000 |
| 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 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".