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Record W2560643631 · doi:10.1109/eumic.2016.7777518

High-performance self-aligned InAs MOSFETs with L-shaped Ni-epilayer alloyed source/drain contact for future low-power RF applications

2016· preprint· en· W2560643631 on OpenAlexaff
Mohamed Ridaoui, Alain-Bruno Fadgie-Djomkam, M. Pastorek, Nicolas Wichmann, Abdelatif Jaouad, Hassan Maher, Sylvain Bollaert

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsInstitut interdisciplinaire d'innovation technologiqueUniversité de Sherbrooke
Fundersnot available
KeywordsTransconductanceMaterials scienceElectrical engineeringOptoelectronicsPhysicsAnalytical Chemistry (journal)TransistorChemistryVoltageEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

In this study, InAs metal-oxide-semiconductor field effect transistors (MOSFETs) ultra-thin body (UTB) were fabricated with self-aligned method. 4 nm thick Al2O3gate oxide was deposited by Atomic Layer Deposition (ALD) technique. Ni-alloyed ohmic contacts for n-type source and drain (S/D) regions were formed at low annealing temperature (250°C). For a MOSFET with a gate length (LG) of 150 nm, we obtained a maximum drain current (Ion) of 700 mA/mm, and the extrinsic transconductance (GM, max) showed a peak value of 500 mS/mm. The devices exhibited a current gain cutoff frequency fTof 100 GHz and maximum oscillation frequency fMAXof 60 GHz for drain to source voltage (VDS) of 0.7 V.

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 head0.006
GPT teacher head0.202
Teacher spread0.196 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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