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Record W2159320170 · doi:10.1109/jlt.2008.927752

Modeling Defect Enhanced Detection at 1550 nm in Integrated Silicon Waveguide Photodetectors

2009· article· en· W2159320170 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Lightwave Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicIntegrated Circuits and Semiconductor Failure Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsResponsivitySilicon on insulatorPhotodetectorOptoelectronicsDetectorSiliconMaterials scienceSensitivity (control systems)Electronic engineeringWaveguideOpticsPhysicsEngineering

Abstract

fetched live from OpenAlex

Recent attention has been attracted by photo-detectors integrated onto silicon-on-insulator (SOI) waveguides that exploit the enhanced sensitivity to subbandgap wavelengths resulting from absorption via point defects introduced by ion implantation. In this paper, we present the first model to describe the carrier generation process of such detectors, based upon modified Shockley-Read-Hall generation/recombination, and, thus, determine the influence of the device design on detection efficiency. We further describe how the model may be incorporated into commercial software, which then simulates the performance of previously reported devices by assuming a single midgap defect level (with properties commensurate with the single negatively charged divacancy). We describe the ability of the model to highlight the major limitations to responsivity, and thus suggest improvements which diminish the impact of such limitations.

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.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.205
Teacher spread0.199 · 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