Application of Bragg superlattice filters in low-temperature microrefrigerators
Bibliographic record
Abstract
We propose to use the Bragg interference filter technology for fabrication of microrefrigerators. The idea of using superconductor-insulator-superconductor (SIS) or normal metal-insulator-superconductor (SIN) tunnel junctions as cooling elements in micro-refrigerators is attractive because of the absence of (micro-refrigerators operating below 150 K. There are corresponding experiments [1] on SIN tunnel junctions where an attached to the SIN tunnel junction membrane was cooled down. Theoretical approaches (both phenomenological [1] as well as microscopic [2] show that the cooling effect exists also in 515 tunnel junction. However this was not observed experimentally because of inefficient thermal contact between SIS tunnel junction and the membrane that must be cooled. The microscopic approach to cooling is based on the "phonon deficit effect" [2] in nonequilibrium regime of tunnel junctions. In some circumstances, when the applied voltage does not exceed the superconducting energy gap ( A ) the probability of phonon absorption from the heat-bath is higher than its emission in the nonequilibrium regime of tunnel junctions. There is an appropriate absorption window in the phonon emission spectra [2,3] and by absorbing these phonons from the heat bath the SIS or SIN tunnel junction can refrigerate its environment. This effect can be improved by use of phonon filters placed between the tunnel junction and the heath-bath [4]. Such a filter can be the Bragg interference superlattice (Bragg's grating) which is well studied for problems of optical communications. Bragg interference filters are used also for detection of phonons emitted by tunnel junctions [5]. Usually such filters cut low and high frequencies, and the used detector may detect well separated frequencies. In contrast, to enhance the refrigeration process one needs filters with very broad spectral transmission properties or a large transmission band with one or two narrow stop bands. The type of the needed filter will depend on the types of the used tunnel junction. Corresponding discussion is presented.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".