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Record W2016929793 · doi:10.1109/embc.2013.6610089

Towards on-chip integration of brain imaging photodetecors using standard CMOS process

2013· article· en· W2016929793 on OpenAlexafffund
Ehsan Kamrani, Frédéric Lesage, Mohamad Sawan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Optical Sensing Technologies
Canadian institutionsPolytechnique Montréal
FundersCanadian Institutes of Health ResearchCanada Research ChairsHeart and Stroke Foundation of Canada
KeywordsTransimpedance amplifierAPDSCMOSChipAvalanche photodiodePhotodiodeBandwidth (computing)PhotodetectorOptoelectronicsElectronic engineeringAmplifierMaterials scienceComputer scienceElectrical engineeringEngineeringDetectorOperational amplifierTelecommunications

Abstract

fetched live from OpenAlex

The main effects of on-chip integration on the performance and efficiency of silicon avalanche photodiode (SiAPD) and photodetector front-end is addressed in this paper based on the simulation and fabrication experiments. Two different silicon APDs are fabricated separately and also integrated with a transimpedance amplifier (TIA) front-end using standard CMOS technology. SiAPDs are designed in p+/n-well structure with guard rings realized in different shapes. The TIA front-end has been designed using distributed-gain concept combined with resistive-feedback and common-gate topology to reach low-noise and high gain-bandwidth product (GBW) characteristics. The integrated SiAPDs show higher signal-to-noise ratio (SNR), sensitivity and detection efficiency comparing to the separate SiAPDs. The integration does not show a significant effect on the gain and preserves the low power consumption. Using APDs with p-well guard-ring is preferred due to the higher observed efficiency after integration.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.356

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 head0.015
GPT teacher head0.292
Teacher spread0.277 · 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

Citations0
Published2013
Admission routes2
Has abstractyes

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