Structural and optical characterizations of Yb3+ doped GeO2-PbF2-PbO glass-ceramics for optical refrigeration
Bibliographic record
Abstract
We report on the structural and optical properties of 50GeO2-30PbF2-(20-x)PbO-xYbF3, with x = 0.5, 1.5, 2.0, 2.5 mol% glass-ceramics for optical refrigeration. XRD measurements reveal the formation of nanocrystals embedded in glass samples after heat treatment at 360°C ⁄ 20h. Spectroscopic measurements show that samples have near infrared photoluminescence emission due to the 2F5/2 − 2F7/2 Yb3+ transition, centered at ∼1020 nm with excitation at 919.7 nm, or 1011.2 nm, and the highest PL emission efficiency occurs for samples with 2.0 mol% of Yb3+. The PL quantum yield varies between 95% and 75%, depending on the lanthanide concentration and excitation wavelength, for 1.5 and 2.5 mol% Yb3+doped samples being the most efficient under 1011.2 nm excitation. The UV-Vis-NIR spectroscopy shows a transparency as high as 80% in the infrared region, and the absorption between 900-1050 nm increases with Yb3+ concentration, in good agreement with the theoretical doping levels. Preliminary measurements monitoring the sample temperature dependence using a fiber Bragg grating sensor, as a function of pump laser wavelength and Yb3+ concentration shows that the heating process approaches zero for an excitation wavelength of around 1030 nm, which is an indication that phonons are annihilated in these glass-ceramic materials, and shows promise for applications in optical refrigeration.
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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".