Demonstration of Power-over-Fiber with Watts of Output Power Capabilities over Kilometers or at Cryogenic Temperatures
Bibliographic record
Abstract
We demonstrate the use of laser diodes and multijunction photovoltaic power converters to efficiently deliver watts of electrical power for long-distance or cryogenic applications. Transmission through single-mode and multi-mode fibers at the wavelengths of 808 nm and 1470/1550 nm are studied. An electrical output power of ~0.1 W is obtained after a 5 km transmission through a standard single-mode SMF28 fiber fed with 0.25 W of optical power. An electrical output power of ~1 W is demonstrated after a 5 km transmission with a standard OM1 multi-mode fiber fed with ~2.5 W. Photovoltaic conversion efficiencies reaching Eff ~49% are obtained with an output voltage of ~5 V using commercial multijunction laser power converters. For low-temperature applications, an ultra-sensitive silicon photomultiplier (SiPM) is used to detect the residual light leaked from fibers as the temperature is decreased. Our study demonstrates that specific fiber types enable low-loss transmission compatible with cryogenic requirements and without light leakage triggering of the SiPM. A cryogenic power-over-fiber system at ~1470 nm is demonstrated with ~2 W of electrical power converted over a 10 m distance having a conversion efficiency of Eff > 65% at 77 K.
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 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".