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Record W2921305690 · doi:10.1109/jeds.2019.2903541

A 6-TFT Charge-Transfer Self-Compensating Pixel Circuit for Flexible Displays

2019· article· en· W2921305690 on OpenAlexafffund
Qing Li, Czang-Ho Lee, Mohsen Asad, William S. Wong, Manoj Sachdev

Bibliographic record

VenueIEEE Journal of the Electron Devices Society · 2019
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Waterloo
FundersUniversity of Waterloo
KeywordsThin-film transistorMaterials sciencePolyethylene naphthalatePixelOptoelectronicsTransistorFlexible displayLogic gateThreshold voltageStress (linguistics)Electrical engineeringElectronic engineeringVoltageComputer scienceEngineeringComposite materialArtificial intelligencePolyethylene terephthalate

Abstract

fetched live from OpenAlex

In this paper, a self-compensating 6 thin-film transistor (TFT) pixel circuit with special layout considerations has been proposed to mitigate the impact of the electrical instability of hydrogenated amorphous silicon TFTs as well as applied mechanical strain. The proposed pixel circuit has been fabricated onto flexible polyethylene naphthalate (PEN) substrate and the measurement results demonstrated less than ±3% variation of its output current after an accelerated 24-h stress test under flat, tensile strain, and compressive strain conditions. In addition, the proposed pixel circuit only required a pair of signals to operate, which reduced the complexity on external IC drivers.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.743

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 integrity0.0000.001
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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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

Citations18
Published2019
Admission routes2
Has abstractyes

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