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Record W2471820840 · doi:10.5539/apr.v8n4p11

A New Kinetics Defect Diffusion Model and the Critical Current Density of Semiconductor Laser Degradation

2016· article· en· W2471820840 on OpenAlexvenueno aff
Jack Jia‐Sheng Huang, Yu‐Heng Jan

Bibliographic record

VenueApplied Physics Research · 2016
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsnot available
Fundersnot available
KeywordsElectromigrationDiffusionExtrapolationMaterials scienceCurrent densityLaserDegradation (telecommunications)DiodeLog-normal distributionSemiconductorReliability (semiconductor)OptoelectronicsPhysicsThermodynamicsElectronic engineeringOptics

Abstract

fetched live from OpenAlex

Critical current density on the electromigration failure is a commonly observed phenomenon in the integrated circuit (IC) interconnect. The critical current density is important for the lognormal distribution and failure time extrapolation of IC metal conductors. In this paper, we report the critical current density (jc) of semiconductor laser degradation for the first time. Despite of the different physical origin, the jc of the laser degradation exhibits similar effect on the failure time distribution. We develop a new kinetic defect diffusion model that can account for the existence of jc. We discuss the physical mechanism and its implication in the reliability extrapolation of diode lasers.

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 score0.003
Threshold uncertainty score0.010

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 studies0.0000.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0020.001
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 head0.060
GPT teacher head0.324
Teacher spread0.264 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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