One-pot microemulsion synthesis of luminescent core@shell lanthanide-doped nanoparticles
Bibliographic record
Abstract
The optical properties of lanthanide-doped nanoparticles depend on the location of dopant ions. Doped (H3O)Y3F10@(H3O)Y3F10 core@shell nanoparticles were synthesized in a one-pot inverse microemulsion involving multiple additions of precursors, leading to the isolation of the lanthanide ions in the core or the shell. This synthesis provides excellent control of shell growth without secondary nucleation. Elemental analysis, electron microscopy, and electron spectroscopy revealed the doping level and ion localization. Heavier lanthanide ions, such as Er3+, can completely replace Y3+ in the host matrix (H3O)Y3F10 without crystal structure modification; (H3O)Er3F10 can be prepared either as a shell or a core material. Lighter lanthanide ions, such as Eu3+, however, are only tolerated in the (H3O)Y3F10 matrix up to ∼15%. Eu-doped (H3O)Y3F10 nanoparticles show well-defined emission spectra, consistent with high crystallinity. The emission intensity varies with Eu doping levels, even after normalization for Eu content. The addition of an undoped shell to Eu-doped cores increases luminescence, which varies significantly with the core doping level. Luminescence decay curves, fitted as biexponentials, yield lifetimes on the order of 2 and 4 ms. For 5% Eu cores, the relative contribution of the shorter lifetime to overall emission decreases upon the addition of an undoped shell, consistent with the protection of emissive surface sites from environmental quenching. Even with uniform, well-defined shells, lighter lanthanide dopant segregation is hampered by potential ion migration. This work demonstrates not only the importance of developing syntheses permitting the controlled localization of doping ions but also the necessity of validating ion distribution in nanoparticles.
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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) | 0.001 | 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 | 0.001 |
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".