Size-Dependent Maximization of Upconversion Efficiency of Citrate-Stabilized β-phase NaYF<sub>4</sub>:Yb<sup>3+</sup>,Er<sup>3+</sup> Crystals via Annealing
Bibliographic record
Abstract
Upconversion materials show great potential in converting infrared light to visible for many optoelectronic and photovoltaic devices. One of the most promising upconverting materials is Yb(3+),Er(3+)- doped β-NaYF4. In this study, annealing is shown to have a significant impact on the phase, morphology, and upconversion luminescence of β-NaYF4:Yb(3+),Er(3+) crystals of varying sizes (300 nm, 700 nm, and 2.3 μm, respectively) prepared by hydrothermal synthesis stabilized with sodium citrate. Upconversion luminescence is maximized via annealing while maintaining crystal shape and size dispersity up to a temperature dependent on initial size, with NIR-to-visible quantum yields of 2-5%. Further temperature increases result in growth and agglomeration, increasing luminescence, followed by transformation to the α-cubic phase resulting in decreases in overall upconversion performance and shifts to dominant red emission. This study establishes the critical link between annealing temperature and maximal upconversion luminescence in β-NaYF4:Yb(3+),Er(3+) crystals, while maintaining particle morphology, which can be very important for technological application.
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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".