Fabrication and Characterization of a High-Power Assembly With a 20-Junction Monolithically Stacked Laser Power Converter
Bibliographic record
Abstract
An increasing number of applications require an electrical source with good insulation and high power. Power over fiber (POF) technology has excellent insulating characteristics and thus is attracting increasing attention. The high-voltage laser power converter (HVLPC) is the most important component in the entire POF system, and the monolithically stacked HVLPC, because of its excellent performance characteristics, is particularly suitable for the requirements of high power. In this paper, we designed and prepared a compact high-power assembly with a 20-junction monolithically stacked HVLPC, and the performance characteristics of the designed assembly were separately tested under laser powers from 2 to 43 W with an 808 nm wavelength. More than 20 W of electric power was extracted under 43 W of laser power, and a maximum photon-energy conversion efficiency of 50.4% was observed with an open-circuit voltage of 22.15 V. Additionally, the temperature characteristics of the designed assembly under different laser powers and different loads were separately discussed, and a three-dimensional thermal simulation model for the designed assembly was established to predict the optimized passive heat sink structure. According to the research conclusions in this paper, additional types of high-power assemblies can be similarly designed in the future.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".