Observation of anti-Stokes-fluorescence cooling in a ZBLAN fiber with a Yb-doped cladding
Bibliographic record
Abstract
This paper reports the first experimental observation of anti-Stokes cooling of fibers in which both the core and the cladding doped with Yb3+ to increase to number of Yb ions contributing to cooling and induce greater refrigeration. Two ZBLAN fibers were designed, fabricated by Le Verre Fluoré, and evaluated experimentally. Two cladding profiles were tested, both with asymmetric boundaries to induce greater mode mixing, and therefore better pump filling of the fiber and greater cooling. Temperature measurements showed that the fiber with a double-D cladding did not perform as well (it cooled to –78 mK for 240 mW of input pump power at 1025.5 nm) largely due to limited mode mixing. The octagonal cladding profile of the second fiber produced greater cooling, down to –1.3 K with 3 W. Fitting experimental results to a model showed good agreement with theory, and confirmed the high critical quenching concentration (Nc = 3.2x1027 Yb/m3), low absorptive background loss (40 dB/km), and good filling ratio (~38%) achieved in this second fiber. This study establishes that with straightforward improvement in mode filling, a cladding-pumped ZBLAN fiber can readily be cooled to ~10 K below room temperature at atmospheric pressure with only ~15 W of pump power.
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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) | 0.000 | 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".