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Record W4409641226 · doi:10.1109/jeds.2025.3562575

A Low Static-Power D Flip-Flop With Unipolar Thin Film Transistors on a Flexible Substrate

2025· article· en· W4409641226 on OpenAlexaff
Shubham Ranjan, Sparsh Kapar, Czang-Ho Lee, William S. Wong, Manoj Sachdev

Bibliographic record

VenueIEEE Journal of the Electron Devices Society · 2025
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsFlip-flopMaterials scienceSubstrate (aquarium)TransistorOptoelectronicsThin-film transistorElectrical engineeringPower (physics)PhysicsCMOSVoltageEngineeringNanotechnology

Abstract

fetched live from OpenAlex

There is increasing interest in affordable and flexible electronics, driven by the need for displays, conformable body sensors, and internet-of-things (IoT) gadgets. Amorphous silicon (a-Si:H), transition metal oxides, and organic thin-film transistors (TFTs) have demonstrated cost-effective large-scale production. As TFTs are typically unipolar in nature, they pose challenges for implementing CMOS-like circuits. Conventional methods to realize circuits in these technologies often lead to restricted voltage swing and excessive direct path current. While several methods have been proposed to counter the voltage swing issue, these methods fail to address the direct path current problem. This article presents low static-power D flip-flops (DFFs) using unipolar TFTs, which significantly reduces the direct path current. The proposed and conventional DFF designs were fabricated on a glass and flexible substrate using a-Si:H TFTs. Additionally, the impact of bending the flexible substrates was examined to assess the robustness and performance of the DFFs under mechanical strain. The measurement results show that the proposed design based DFF saves average total power by 79.8% compared to conventional design.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.786
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
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 head0.227
Teacher spread0.220 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Journal of the Electron Devices SocietySame topicAdvancements in Semiconductor Devices and Circuit DesignFrench-language works237,207