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Record W4416798008 · doi:10.1109/jflex.2025.3638974

A Flexible Decoder With Charge-Sharing Feature for TFT Display Backplanes

2025· article· W4416798008 on OpenAlexaff
Sparsh Kapar, Shubham Ranjan, Czang-Ho Lee, William S. Wong, Manoj Sachdev

Bibliographic record

VenueIEEE Journal on Flexible Electronics · 2025
Typearticle
Language
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBackplaneCMOSFeature (linguistics)TransistorPower (physics)Electronic circuitLiquid-crystal displayPower consumptionLogic gateThin-film transistor

Abstract

fetched live from OpenAlex

Thin-film Transistors (TFTs) have garnered recent research interest in the development of flexible displays, due to their low fabrication costs and high-volume production. In displays, driver circuits are typically implemented with off-panel CMOS logic, while the display pixels themselves use TFTs. This approach restricts the resolution enhancement of displays and causes significant power dissipation. Additionally, implementing CMOS-like logic with unipolar TFTs requires careful attention to power and voltage swing. The latest bootstrapped inverter technology has addressed some of these issues, demonstrating the use of unipolar TFTs in row-driver display circuits. In this article, we propose a row address decoder circuit for TFT-based displays that reduces dynamic power consumption through charge-sharing on glass and flexible substrate. The impact of bending and substrate material was also investigated. Measurement results show that the proposed design-based 3-to-8 decoder under various conditions saves on average 26.0% of the power compared to a state-of-the-art TFT-based decoder.

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), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.623
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.005
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 head0.011
GPT teacher head0.255
Teacher spread0.243 · 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 designNot applicable
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
Published2025
Admission routes1
Has abstractyes

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