Intense NIR emissions at 0.8 μm, 1.47 μm, and 1.53 μm from colloidal LiYbF<sub>4</sub>:Ln<sup>3+</sup> (Ln = Tm<sup>3+</sup> and Er<sup>3+</sup>) nanocrystals
Bibliographic record
Abstract
We report on the synthesis of diamond shaped Ln(3+)-doped LiYbF4 (Ln = Tm and Er) nanocrystals with flat edges via the thermal decomposition method. Strong near-infrared emissions at 0.8 μm, 1.47 μm and 1.53 μm are observed from colloidal dispersions of Tm(3+)-doped and Er(3+)-doped LiYbF4 nanocrystals, respectively, under 0.98 μm diode laser excitation. The NIR emission intensities for Tm(3+)-doped and Er(3+)-doped LiYbF4 nanocrystals are comparable with those of the sodium counterpart NaYbF4, suggesting that LiYbF4 is also an excellent host matrix for lanthanide ions to obtain strong NIR emissions in colloidal solutions of LiYbF4 (Tm(3+) or Er(3+)) nanocrystals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".