Near-Infrared-to-Blue Upconversion in Colloidal BaYF<sub>5</sub>:Tm<sup>3+</sup>, Yb<sup>3+</sup> Nanocrystals
Bibliographic record
Abstract
Tetragonal barium yttrium fluoride (BaYF 5 ) nanocrystals doped with 0.5 mol % Tm 3+ and 15 mol % Yb 3+ (BaYF 5:Tm 3+, Yb 3+ ) were synthesized using the thermal decomposition method yielding rectangular-shaped nanocrystals (15 nm × 5 nm) that can (up)convert near-infrared light to higher energies such as blue, via a process known as upconversion. The upconversion spectrum of the BaYF 5:Tm 3+, Yb 3+ nanocrystals, following excitation with 980 nm, revealed that the upconverted blue emission from the 1 G 4 → 3 H 6 transition was more intense than the infrared 3 H 4 → 3 H 6 emission at high excitation densities (90 W/cm 2 ) contrary to what is normally observed for Tm 3+ /Yb 3+ codoped nanomaterials. On the other hand, the infrared emission dominates at lower excitation densities (15 W/cm 2 ) demonstrating a lack of excited Yb 3+ ions to carry on the upconversion beyond the 3 H 4 excited state to the 1 G 4 excited state. A saturation of the upconversion process was observed in the power dependence studies at excitation densities above 57 W/cm 2, causing a deviation in the expected number of photons required for the upconversion process. The upconversion properties of BaYF 5:Tm 3+, Yb 3+ nanocrystals are elucidated and discussed.
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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) | 0.000 | 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 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".