LiAl5O8:Fe3+ and LiAl5O8:Fe3+, Nd3+ as a New Luminescent Nanothermometer Operating in 1st Biological Optical Window
Bibliographic record
Abstract
New types of contactless luminescence nanothermometers, namely, LiAl5O8:Fe3+ and LiAl5O8:Fe3+, Nd3+ are presented for the first time, revealing the potential for applications in biological systems. The temperature-sensing capability of the nanocrystals was analyzed in wide range of temperature (−150 to 300 °C). The emission intensity of the Fe3+ ions is affected by the change in temperature, which induces quenching of the 4T1 (4G) → 6A1 (6S) Fe3+ transition situated in the 1st biological window. The highest relative sensitivity in the temperature range (0 to 50 °C) was found to be 0.82% °C (at 26 °C) for LiAl5O8: 0.05% Fe3+ nanoparticles that are characterized by long luminescent lifetime of 5.64 ms. In the range of low and high temperatures the Smax was calculated for LiAl5O8:0.5% Fe3+ to be 0.92% °C at −100 °C and for LiAl5O8:0.01% Fe3+ to be 0.79% °C at 150 °C. The cytotoxicity assessment carried out on the LiAl5O8:Fe3+ nanocrystals, demonstrated that they are biocompatible and may be utilized for in vivo temperature sensing. The ratiometric luminescent nanothermometer, LiAl5O8:Fe3+, Nd3+, which was used as a reference, possesses an Smax = 0.56%/°C at −80 °C, upon separate excitation of Fe3+ and Nd3+ ions using 266 nm and 808 nm light, respectively.
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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".