Mie Resonance Enhancement of Laser Cooling of Rare- earth Doped Nanospheres
Bibliographic record
Abstract
Laser cooling of solids with anti-Stokes fluorescence is currently attracting widespread attention because of the wide range of its applications, including all-optical cryocooling for airborne and space-based applications, heat suppression in high-power lasers, and cooling of nanoparticles for biological and mesoscopic physics. This laser cooling process has typically very low (only a few%) efficiency and its enhancement is therefore highly desirable. In this work, we propose to leverage Mie resonance to enhance anti-Stokes fluorescence cooling in RE-doped nanoparticles. As an example, we consider an Yb 3+ :YAG nanosphere pumped at the long wavelength tail of the Yb 3+ absorption spectrum, at 1030 nm. We show that if the radius of the nanosphere is adjusted to the pump wavelength in such a manner that the pump excites some of the Mie resonant modes of the sample, the cooling power density generated in the sample is considerably enhanced and the temperature of the sample is consequently appreciably decreased.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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".