MétaCan
Menu
Back to cohort
Record W3162079543 · doi:10.1364/optica.425115

Radiation-balanced silica fiber laser

2021· article· en· W3162079543 on OpenAlexafffund
Jennifer M. Knall, Magnus Engholm, Tommy Boilard, Martin Bernier, P. Vigneron, Nanjie Yu, Peter D. Dragic, John Ballato, Michel J. F. Digonnet

Bibliographic record

VenueOptica · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOptical properties and cooling technologies in crystalline materials
Canadian institutionsUniversité Laval
FundersAir Force Office of Scientific ResearchNatural Sciences and Engineering Research Council of Canada
KeywordsAnalytical Chemistry (journal)Materials scienceChemistryChromatography

Abstract

fetched live from OpenAlex

In optically pumped lasers, heat generated by the quantum defect causes detrimental fluctuations in the output mode, frequency, and power. Common heat-mitigation techniques use bulky mechanical coolers that introduce vibrations, leading to laser frequency and amplitude noise. Here, we present a radiation-balanced fiber laser, optically cooled by anti-Stokes fluorescence (ASF). The gain medium is a silica fiber with a 21-µm-diameter core doped with 2.06 wt. % Y b 3 + and co-doped with A l 2 O 3 and F- to reduce concentration quenching. The laser was core-pumped at 1040 nm to create both gain at 1065 nm and ASF cooling at atmospheric pressure. We demonstrate a maximum output power of 114 mW with a slope efficiency of 41% while maintaining near-zero average temperature change. This result could enable the development of fiber lasers with unprecedented coherence and stability.

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 score0.003
Threshold uncertainty score0.010

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.002

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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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

Citations45
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueOpticaSame topicOptical properties and cooling technologies in crystalline materialsFrench-language works237,207