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Resolving Unusual Gate Current and Dielectric Breakdown of Solution Processed Carbon Nanotube Thin Film Transistor

2022· article· en· W4312381555 on OpenAlexafffund
Sean F. Romanuik, Bishakh Rout, Pierre‐Luc Girard‐Lauriault, Sharmistha Bhadra

Bibliographic record

Venue2022 IEEE International Symposium on Circuits and Systems (ISCAS) · 2022
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThin-film transistorDielectricMaterials scienceTransistorGate dielectricLeakage (economics)OptoelectronicsCarbon nanotubeFabricationActive layerNanotechnologyLayer (electronics)Electrical engineeringVoltage

Abstract

fetched live from OpenAlex

The traditional design of solution processed single-walled carbon nanotube (SWCNT) thin film transistors (TFTs) suffers from high leakage currents and are prone to dielectric breakdowns. In this paper, we report the proof of concept of an improved structure for a solution processed SWCNT based TFT. The improved structure TFT has 11,429 times lower gate leakage current than a traditional design TFT of the same dimensions in the on state and exhibits no dielectric breakdown. The gate leakage current in the improved structure is reduced and the dielectric breakdown is resolved by a simple patterning of the SWCNT layer and increasing the thickness of the dielectric layer. In order to take advantage of solution based fabrication techniques, the active layer and the electrodes are fabricated by solution based depositions. The improved structure TFT has a mobility of 0.3 cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> V <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> s <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> and an on/off ratio of approximately 2640. The mobility and on/off ratio can be further improved in the future by increasing the incubation time in the SWCNT solution. In the future, the active and dielectric layers of this structure will be printed and the TFT will be miniaturized, to produce entirely printed SWCNT TFTs and circuits.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.759
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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 designSimulation or modeling
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

Citations4
Published2022
Admission routes2
Has abstractyes

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