Upconverting nanoparticles as primary thermometers and power sensors
Bibliographic record
Abstract
Luminescence thermometry is a spectroscopic technique for remote temperature detection based on the thermal dependence of the luminescence of phosphors, presenting numerous applications ranging from biosciences to engineering. In this work, we use the Er 3+ emission of the NaGdF 4 /NaGdF 4 :Yb 3+ ,Er 3+ /NaGdF 4 upconverting nanoparticles upon 980 nm laser excitation to determine simultaneously the absolute temperature and the excitation power density. The Er 3+ 2 H 11/2 → 4 I 15/2 and 4 S 3/2 → 4 I 15/2 emission bands, which are commonly used for thermometric purposes, overlap with the 2 H 9/2 → 4 I 13/2 emission band, which can lead to erroneous temperature readout. Applying the concept of luminescent primary thermometry to resolve the overlapping Er 3+ transitions, a dual nanosensor synchronously measuring the temperature and the delivered laser pump power is successfully realized holding promising applications in laser-supported thermal therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".