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Record W1971255610 · doi:10.1116/1.1730328

Modeling of mushroom waveguide photodetector

2004· article· en· W1971255610 on OpenAlexaff
Yasser M. El-Batawy, M. Jamal Deen

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2004
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPhotodetectorParasitic extractionOptoelectronicsMaterials scienceCapacitanceResistorEquivalent series resistanceInductorBandwidth (computing)Computer sciencePhysicsElectrodeElectrical engineeringEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Waveguide photodetectors (WGPDs) are promising candidates for applications in high-speed optical communications and interconnections. In these high-speed photodetectors, both high bandwidth and high external quantum efficiency can be achieved simultaneously. Mushroom-WGPD is proposed to overcome the trade-off between the capacitance and contact resistance of the photodetector. In this article, a physical model of the mushroom-WGPD is presented including both time and frequency responses of this photodetector and how they depend on the parameters of the photodetector. A SPICE model for mushroom-WGPD including all the parasitics is also presented, showing the dependence of the transfer function of this model on the dimensions and the material parameters of the photodetector. The effects of the parasitics are also studied for different photodetector areas. The characteristics of mushroom-WGPD are studied for two cases, first without an inductor added in series with the load resistance and second, if an inductor is added in series to the load resistor. A significant improvement in performance is achieved in the second case where an inductor is added.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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

Citations7
Published2004
Admission routes1
Has abstractyes

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