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Record W4362669720 · doi:10.1002/adma.202370104

A Wafer‐Scale Nanoporous 2D Active Pixel Image Sensor Matrix with High Uniformity, High Sensitivity, and Rapid Switching (Adv. Mater. 14/2023)

2023· article· en· W4362669720 on OpenAlexaff
Heekyeong Park, Anamika Sen, Manasa Kaniselvan, AbdulAziz AlMutairi, Arindam Bala, Luke P. Lee, Youngki Yoon, Sunkook Kim

Bibliographic record

VenueAdvanced Materials · 2023
Typearticle
Languageen
FieldEngineering
TopicGas Sensing Nanomaterials and Sensors
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNanoporousMaterials scienceWaferActive matrixPixelNanoscopic scaleImage sensorSensitivity (control systems)OptoelectronicsNanotechnologyCMOSMatrix (chemical analysis)Electronic engineeringComputer scienceArtificial intelligenceThin-film transistorEngineering

Abstract

fetched live from OpenAlex

Image Sensor Devices In article number 2210715, Luke P. Lee, Youngki Yoon, Sunkook Kim, and co-workers present a novel active pixel image sensor matrix using large-area nanoporous MoS2, which achieves ultrahigh sensitivity and fast switching ability. This study represents significant conceptual and practical advancements in image sensor devices based on 2D materials, including wafer-scale synthesis, nanoscale patterning, rigorous modeling, and optoelectrical analysis. These advancements could potentially lead to the replacement of complementary metal–oxide–semiconductor (CMOS) technology in the near future.

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 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 score0.010
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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