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Record W2160559300 · doi:10.1109/jssc.2011.2157254

CMOS Technology Scaling Considerations for Multi-Gbps Optical Receivers With Integrated Photodetectors

2011· article· en· W2160559300 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2011
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoIntel Corporation
KeywordsPhotodetectorCMOSResponsivityPhotodiodeElectronic engineeringBandwidth (computing)Computer scienceEqualization (audio)ScalingOptical communicationOptoelectronicsMaterials scienceTelecommunicationsEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

The integration of photodetectors for optical communication into standard nanoscale CMOS process technologies can enable low cost for emerging high volume short-reach parallel optical communication. Whereas past work has highlighted the challenges that face integrated photodetectors in highly scaled CMOS technologies, this work examines the opportunities afforded by these new technologies. First, scaling promises improved extrinsic photodetector bandwidth thanks to improved TIA performance. Second, modern advanced process features enable new photodetector structures with improved performance. A phototransistor employing deep n-wells is characterized in 65-nm CMOS and exhibits a more than ten-fold increase in responsivity over a similar structure without the buried n-well. Third, equalization techniques benefit from technology scaling and are only just beginning to be applied to CMOS integrated photodetectors. In particular, decision feedback equalization appears to offer potential for 10+ Gbps operation.

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 score0.126
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.051
GPT teacher head0.257
Teacher spread0.206 · 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