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Record W1989533628 · doi:10.1117/12.567181

Two-dimensional sensor array for low-level light detection

2004· article· en· W1989533628 on OpenAlexafffund
Jeff Hsin Chang, Y. Vygranenko, Arokia Nathan

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhotodiodeOptoelectronicsMaterials scienceDiodeTransistorLeakage (economics)WaferFabricationDetectorOpticsElectrical engineeringVoltagePhysics

Abstract

fetched live from OpenAlex

This paper presents the design, fabrication process, and performance evaluation of a two-dimensional hydrogenated amorphous silicon (a-Si:H) n-i-p photodiode array, developed specifically for low-level light sensor applications. The design of the device is simpler than conventional active-matrix-arrays with thin-film transistor (TFT) addressing electronics, owing to the utilization of the a-Si:H switching diodes for signal readout. Since both sensor diodes and switching diodes are formed simultaneously through dry etching the entire wafer area, the mask count required for lithography is reduced to six. The most challenging problem associated with the fabrication of these devices is the excess leakage current, which inherently limits the output signal-to-noise ratio and dynamic range. The reverse dark current in the photodiodes were minimized by tailoring the defects at the i-p interface. The junction-edge leakage current in the switching diodes is associated with damage caused by ion bombardment, and can be reduced by optimizing of the plasma processing conditions. A 3×4 pixels array prototype was tested using a specially designed test board which performs pre-amplification, double sampling and final amplification for each column of the array. Details of the signal readout process along with detector performances are presented and discussed.

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 categoriesMeta-epidemiology (narrow)
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 score0.186
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.216
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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
Published2004
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicCCD and CMOS Imaging SensorsFrench-language works237,207