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Record W2046001755 · doi:10.1364/ol.38.001633

High-power diode laser bars and shear strain

2013· article· en· W2046001755 on OpenAlexaff
Daniel T. Cassidy, Othman Rehioui, Chadwick K. Hall, Laurent Béchou, Yannick Deshayes, A. Kohl, T. Fillardet, Yves Ousten

Bibliographic record

VenueOptics Letters · 2013
Typearticle
Languageen
FieldEngineering
TopicLaser Design and Applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsOpticsMaterials scienceLasing thresholdLaserBirefringenceShear (geology)Polarization (electrochemistry)DiodeSemiconductor laser theoryOptoelectronicsPhysicsComposite material

Abstract

fetched live from OpenAlex

The emitters at the edges of high-power laser bars tend to produce less power than emitters that are near the center of the bar. We suggest that shear strain, which owes to strain induced by bonding, creates through a photoelastic effect a weak birefringence that rotates the plane of polarization of the light. A rotation of the plane of polarization reduces the net gain for the lasing modes and hence leads to a lower output power for the emitters at the edges of the bars, where the shear strain is dominant.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.174
Teacher spread0.169 · 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

Citations11
Published2013
Admission routes1
Has abstractyes

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