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Record W2000128528 · doi:10.1116/1.1689299

Deep-ultraviolet-induced damage of charge coupled device sensors

2004· article· en· W2000128528 on OpenAlexafffund
Flora Li, Arokia Nathan, O Nixon

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2004
Typearticle
Languageen
FieldEngineering
TopicCCD and CMOS Imaging Sensors
Canadian institutionsDalsa CorporationUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsUltravioletCharge-coupled deviceOptoelectronicsMaterials scienceExcimer laserResponsivityOxideDark currentWavelengthImage sensorOpticsLaserPhotodetectorPhysics

Abstract

fetched live from OpenAlex

In order to facilitate the inspection of deep-submicron features, a generation of semiconductor inspection systems are being pushed to image using deep-ultraviolet (UV) sensitive cameras at increasingly shorter wavelengths. In this article, we present a deep-UV sensitive thinned front-illuminated linear charge coupled device (CCD) image sensor structure and investigate its behavior after exposure to F2 (λ=157 nm) excimer laser. Two key manifestations of radiation damage are observed: (1) Extrinsic quantum efficiency drifts with increasing 157 nm exposure, and (2) dark current increases almost exponentially with 157 nm exposure. These fluctuations in CCD parameters can be caused by several factors including UV-induced color center formation in the oxide, charge generation in the oxide, interface modification, and structural rearrangement. These UV-induced effects alter the optical and electrical properties of the oxide and Si–SiO2 interface, resulting in both temporal and permanent shifts in device performance. The experimental results suggest that careful control of the oxide thickness and the Si–SiO2 interface quality are critical for realizing CCD sensors with high responsivity and stability for deep-UV imaging.

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 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 score0.087
Threshold uncertainty score0.882

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.230
Teacher spread0.222 · 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

Citations1
Published2004
Admission routes2
Has abstractyes

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