The Internal Structure of Lanthanide-Doped Nanoparticles and the Effect of High-Temperature Annealing on Their Luminescent Properties
Bibliographic record
Abstract
Up-converting nanoparticles are widely studied for a wide range of applications based on their unique optical properties, with NaYF4 nanoparticles doped with Yb3+ and Er3+ receiving particular attention. While developing this material in nanoparticle form extends their potential applications, the resulting nanoparticles have proven less efficient up-converters than their bulk counterpart. Reported up-conversion quantum yields are significantly lower, even when very thick shells were grown to eliminate quenching by surface defects and surface-bound molecules. This raises the question whether the internal structure of these particles contributes to the lower quantum yield. In our work, we investigated the internal structure of NaYF4:Yb3+ and Er3+ NPs using high-resolution scanning energy dispersive X-ray spectroscopy, generating two-dimensional elemental maps. We deduced that the ions are not distributed homogeneously in the nanoparticles as made via a colloidal synthesis route. Heating the nanoparticles to temperatures used to anneal bulk crystals resulted in a homogeneous distribution, but an increase in emission intensity under similar measurement conditions was not observed. Vibrational spectroscopy showed the presence of OH– in dried nanoparticles, which might act as an internal quencher.
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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 | 0.001 | 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 | 0.001 |
| 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".