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Record W2051370270 · doi:10.1063/1.1589594

Analytical model for saturable aging in semiconductor lasers

2003· article· en· W2051370270 on OpenAlexaff
S. K. K. Lam, R. E. Mallard, Daniel T. Cassidy

Bibliographic record

VenueJournal of Applied Physics · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSigmoid functionSemiconductor laser theoryDiodeCurrent (fluid)LaserSemiconductorMaterials scienceConstant (computer programming)Time constantOpticsOptoelectronicsPhysicsThermodynamicsComputer scienceEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

We present an expression for the change in threshold current of a semiconductor laser diode as a function of the aging time under constant thermal and current aging. The expression forms a sigmoidal shape with the aging time, and is accurate in describing the increase of threshold current during aging. In the case where nonlinearities or “knees” occur in the threshold current aging curve, a multicomponent defect model is utilized to explain the observation. This multicomponent defect model allows multiple sigmoidal curves to be incorporated into the description. Each sigmoidal curve is thought to represent the growth of one type of defect complex. The parameters in the model are designed to have physical meaning that corresponds to the properties of the laser material. The model is compared to five popular models used to describe the threshold current aging characteristics.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.025
GPT teacher head0.275
Teacher spread0.250 · 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 designSimulation or modeling
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

Citations24
Published2003
Admission routes1
Has abstractyes

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