Enhancing the optical performance of oxyfluoride glass ceramics by optimizing the oxide: Fluoride ratio and crystallinity for optical refrigeration
Bibliographic record
Abstract
The optimization of the oxide and fluoride content, crystallinity and rare earth ion concentration in oxyfluoride glass ceramics (GCs) are of great importance in obtaining high photoluminescence quantum yield (PLQY) for optical refrigeration applications. Presented herein are the important advancements in the development of a novel oxyfluoride GCS of the composition (SiO2-Al2O3)(100-a) (YLiF4)b: (YbF3)b (a = 35 and 40; in mol %, b = 1 and 2 mol%) with the corresponding parent glasses with an in-depth investigation on enhancing the optical performance for laser cooling. Depending on the oxide/fluoride (O/F) ratio and ytterbium content the internal quantum yield (iQY) varied between 70 and 99% in glass ceramics at several excitation wavelengths. The optical properties of GCs containing YLiF4 and YF3 nanocrystals obtained from the same initial composition (modulated by time and fusion temperature) were compared to find the optimal composition for optical refrigeration. Low fluorine content led to the generation of YLiF4 as a major phase after ceramization and high fluorine content helped in the generation of the YF3 phase. An increase in the radiative lifetime of YF3 GCs compared to YLiF4 GCs has been found to coincide with the enhancement of the PLQY, which is beneficial for laser cooling. The temperature change (ΔT) change measured using a fiber Bragg grating (FBG) in the glass and glass-ceramic samples with different pump wavelengths showed significant heat mitigation near ∼1030 nm. The observed enhanced PL intensity, iQY and lifetime after purification of YLiF4 glasses imply that the purity of the material plays a paramount role in lowering the background absorption and enhancing the quantum yield. Looking ahead, we see a bright future for oxyfluoride GCs in applications requiring the ultimate levels of thermal, mechanical and optical performance, especially for the development of cryocooler devices, which are still technologically challenging and expensive. The usage of GCs will open up new possibilities in optical cooling technology, enabling cooling devices of any size and shape.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".