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Record W1969717826 · doi:10.1116/1.582236

Two-dimensional gain profiles of InP/InGaAs separate absorption, grading, charge, and multiplication avalanche photodiodes modeled by a simplified stochastic approach

2000· article· en· W1969717826 on OpenAlexafffund
Yegao Xiao, M. Jamal Deen

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSemiconductor Quantum Structures and Devices
Canadian institutionsMcMaster UniversitySimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAPDSAvalanche photodiodeElectric fieldPoisson's equationOptoelectronicsImpact ionizationMaterials scienceAvalanche breakdownHeterojunctionAbsorption (acoustics)OpticsPhysicsBreakdown voltageIonizationVoltageDetectorQuantum mechanics

Abstract

fetched live from OpenAlex

The two-dimensional (2D) gain profiles of InP/InGaAs separate absorption, grading, charge, and multiplication (SAGCM) avalanche photodiodes (APDs) have been modeled by using a simplified stochastic approach. The influence of the curved diffusion edge on the electric field in the periphery has been considered and electric field equations have been derived from the cylindrical Poisson’s equation. The electric field in the multiplication layer is significantly reduced when a partial charge sheet is incorporated in the device’s periphery. The modeled 2D gain profile for such a device agrees with experiment and demonstrates an effective suppression of the premature edge breakdown. These results and the uniformity issue of the 2D gain profiles are further discussed. From our analyses, we find that controlling the diffusion process within the p+ InP top layer and patterning the charge sheet mesa structure are most likely to affect the uniformity and symmetry of the 2D gain profiles for the InP/InGaAs SAGCM APDs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.757

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.259
Teacher spread0.248 · 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 teacher head, 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

Citations5
Published2000
Admission routes2
Has abstractyes

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