UV and Temperature-Sensing Based on NaGdF<sub>4</sub>:Yb<sup>3+</sup>:Er<sup>3+</sup>@SiO<sub>2</sub>–Eu(tta)<sub>3</sub>
Bibliographic record
Abstract
Abstract A multifunctional nanosystem was synthesized to be used as a dual sensor of UV light and temperature. NaGdF4:Yb3+:Er3+ upconverting nanoparticles (UCNPs) were synthesized and coated with a silica shell to which a europium(III) complex was incorporated. The synthesis of NaGdF4 UCNPs was performed via thermal decomposition of lanthanide ion fluoride precursors in the presence of oleic acid. To achieve sufficient water dispersibility, the surface of the hydrophobic oleate-capped UCNPs in the hexagonal phase was modified by a silica coating through a modified Stöber process through a reverse microemulsion method. An Eu(tta)3 (tta: thenoyltrifluoroacetonate) complex was prepared in situ at the silica shell. A dual-mode nanothermometer was obtained from a near infrared to visible upconversion fluorescence signal of Er3+ ions together with UV-excited downshifting emission from the Eu3+ complex. Measurements were recorded near the physiological temperature range (293–323 K), revealing excellent linearity (R2 > 0.99) and relatively high thermal sensitivities (≥1.5%·K–1). The Eu(tta)3 complex present in the silica shell was tested as the UV sensor because of the Eu3+ luminescence dependence on UV-light exposure time.
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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".