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Record W2070251136 · doi:10.1116/1.1463073

Dry etch process optimization for small-area<i>a</i>-Si:H vertical thin film transistor

2002· article· en· W2070251136 on OpenAlexafffund
I-Min Chan, Arokia Nathan

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2002
Typearticle
Languageen
FieldEngineering
TopicThin-Film Transistor Technologies
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceFabricationDry etchingEtching (microfabrication)Thin-film transistorTransistorSiliconOptoelectronicsAmorphous solidDeposition (geology)PlasmaPlasma etchingAmorphous siliconThin filmReactive-ion etchingNanotechnologyLayer (electronics)Electrical engineeringCrystalline siliconChemistryCrystallographyGeologyEngineeringVoltage

Abstract

fetched live from OpenAlex

This article reports the investigation of dry etch processes suitable for small-area amorphous silicon (a-Si:H) vertical thin film transistor (VTFT) fabrication. SF6/O2 and CF4/H2 gas mixtures were experimented on for the anisotropic etching of an n+a-Si:H/a-SiNx:H/n+a-Si:H trilayer to give a self-aligned vertical drain–source stacked structure that is desirable for subsequent deposition of the VTFT channel layers. The results show that the trilayer profiles formed with the SF6/O2 plasma for different O2 concentrations suffered different degrees of undercutting of the composite layers under overetching condition, leading to misaligned etch profiles. On the other hand, the CF4/20%H2 plasma provides a self-aligned vertical trilayer profile even after 1 min of overetching.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.016
GPT teacher head0.219
Teacher spread0.203 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2002
Admission routes2
Has abstractyes

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