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Record W2924942253 · doi:10.1364/ol.44.001801

More than 200  W random Raman fiber laser with ultra-short cavity length based on phosphosilicate fiber

2019· article· en· W2924942253 on OpenAlexaff
Jinyan Dong, Lei Zhang, Jiaqi Zhou, Weiwei Pan, Xijia Gu, Yan Feng

Bibliographic record

VenueOptics Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsToronto Metropolitan University
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsMaterials scienceFiber laserLaser linewidthOpticsRaman spectroscopyFiberLaserRaman laserLaser power scalingOptical fiberOptoelectronicsPolarization-maintaining optical fiberRaman scatteringFiber optic sensorPhysics

Abstract

fetched live from OpenAlex

An over 200 W high-power first-order random Raman fiber laser (RRFL) at 1238 nm is demonstrated. The laser is based on a half-open cavity with a piece of 30 m phosphosilicate fiber. This RRFL is pumped by a conventional 1064 nm Yb-doped fiber laser. After suppressing the silica Raman component, a maximum output power of 206.7 W is obtained with a full width half-maximum linewidth of 7.1 nm at a pump power of 346.3 W, corresponding to an optical-to-optical efficiency of 59.7%. To the best of our knowledge, this is the highest reported output power of RRFL on the basis of phosphosilicate fiber with the shortest cavity length.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.005
GPT teacher head0.200
Teacher spread0.195 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations31
Published2019
Admission routes1
Has abstractyes

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