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Record W4380991443 · doi:10.3390/electronics12122695

Near-Infrared CMOS Image Sensors Enabled by Colloidal Quantum Dot-Silicon Heterojunction

2023· article· en· W4380991443 on OpenAlexafffund
Qiwei Xu, Xinghao Tong, Jiangwen Zhang, Xihua Wang

Bibliographic record

VenueElectronics · 2023
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaMitacsAlberta InnovatesKillam Trusts
KeywordsPhotodiodeHeterojunctionCMOSOptoelectronicsMaterials scienceQuantum dotImage sensorSemiconductorIntegrated circuitPixelNear-infrared spectroscopySiliconInfraredNanotechnologyPhysicsOptics

Abstract

fetched live from OpenAlex

The solution processibility of colloidal quantum dots (CQDs) promises a straightforward integration with Si readout integrated circuits (Si-ROCIs), which enables a near-infrared (NIR) CMOS image sensor (CIS; CMOS stands for complementary metal-oxide semiconductor). Previously demonstrated CQD NIR CISs were achieved through integrating CQD photodiode or PhotoFET with Si-ROCIs. Here, we conduct a simulation study to investigate the feasibility of a NIR CIS enabled by another integration strategy, that is, by forming a CQD-Si heterojunction. Simulation results clearly show that each active pixel made of CQD-Si heterojunction photodiode on the CIS sensitively responds to NIR light, and generated photocarriers induce changes in electrostatic potentials in the active pixel. The potential changes are read out through the integrated circuits as validated by the readout timing sequence simulation.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.179
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.003

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2023
Admission routes2
Has abstractyes

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