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Record W2041763400 · doi:10.1116/1.2194933

Nanoscale channel and small area amorphous silicon vertical thin film transistor

2006· article· en· W2041763400 on OpenAlexafffund
Isaac Chan, Saeed Fathololoumi, Arokia Nathan

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2006
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsThin-film transistorAmorphous siliconSubthreshold slopeMaterials scienceOptoelectronicsChannel (broadcasting)TransistorOxide thin-film transistorSiliconAmorphous solidNanoscopic scaleFabricationThreshold voltageNanotechnologyElectrical engineeringVoltageCrystalline siliconEngineeringLayer (electronics)ChemistryCrystallography

Abstract

fetched live from OpenAlex

This article reports the design of vertical thin film transistors (VTFTs) in hydrogenated amorphous silicon (a-Si:H) technology. This transistor structure offers an elegant method of defining the channel length in nanoscale dimensions by means of dielectric film thickness. In addition, the device area of the vertical TFT structure is less than ∼1∕3 that of the ubiquitous lateral TFT structure. We study the deposition mechanisms to gain insight into the fabrication of VTFTs from a conceptual standpoint. The a-Si:H VTFT reported here advances current state of the art, by demonstrating the first 100nm channel length VTFT with an on/off current ratio of 108, threshold voltage of 2.8V, and a subthreshold slope of 0.8V∕decade. This is the shortest and truly vertical channel a-Si:H TFT reported, hitherto. We propose an application of a-Si:H VTFTs in high-resolution flat-panel electronics with TFT size independent fill factor, promising immense benefits in medical x-ray imaging.

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)
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 score0.249
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
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 head0.189
Teacher spread0.180 · 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 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

Citations4
Published2006
Admission routes2
Has abstractyes

Explore more

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