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Record W2040450755 · doi:10.1063/1.3029704

A comparative study of plasma-enhanced chemical vapor gate dielectrics for solution-processed polymer thin-film transistor circuit integration

2008· article· en· W2040450755 on OpenAlexaff
Flora M. Li, Arokia Nathan, Yiliang Wu, Beng S. Ong

Bibliographic record

VenueJournal of Applied Physics · 2008
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsXerox (Canada)University of Waterloo
Fundersnot available
KeywordsPlasma-enhanced chemical vapor depositionMaterials scienceThin-film transistorOptoelectronicsGate dielectricDielectricSilicon nitrideChemical vapor depositionSiliconTransistorGate oxideNanotechnologyLayer (electronics)Electrical engineeringVoltage

Abstract

fetched live from OpenAlex

This paper considers plasma-enhanced chemical vapor deposited (PECVD) silicon nitride (SiNx) and silicon oxide (SiOx) as gate dielectrics for organic thin-film transistors (OTFTs), with solution-processed poly[5,5′-bis(3-dodecyl-2-thienyl)-2,2′-bithiophene] (PQT-12) as the active semiconductor layer. We examine transistors with SiNx films of varying composition deposited at 300 °C as well as 150 °C for plastic compatibility. The transistors show over 100% (two times) improvement in field-effect mobility as the silicon content in SiNx increases, with mobility (μFE) up to 0.14 cm2/V s and on/off current ratio (ION/IOFF) of 108. With PECVD SiOx gate dielectric, preliminary devices exhibit a μFE of 0.4 cm2/V s and ION/IOFF of 108. PQT-12 OTFTs with PECVD SiNx and SiOx gate dielectrics on flexible plastic substrates are also presented. These results demonstrate the viability of using PECVD SiNx and SiOx as gate dielectrics for OTFT circuit integration, where the low temperature and large area deposition capabilities of PECVD films are highly amenable to integration of OTFT circuits targeted for flexible and lightweight applications.

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 score0.137
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.030
GPT teacher head0.235
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.

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

Citations13
Published2008
Admission routes1
Has abstractyes

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