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Record W2561680259

Simulation of High-Frequency Scaling of Silicon MOSFETs and the Golden Transistor

2016· dissertation· en· W2561680259 on OpenAlexaboutno aff
J.D. Bateman

Bibliographic record

VenueTSpace (University of Toronto) · 2016
Typedissertation
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsnot available
Fundersnot available
KeywordsScalingTransistorSiliconMOSFETOptoelectronicsFrequency scalingElectrical engineeringMaterials scienceElectronic engineeringEngineeringMathematicsVoltage
DOInot available

Abstract

fetched live from OpenAlex

This thesis investigates high-frequency scaling of advanced Silicon UTBB-FDSOI MOSFETs using semi-classical and ab initio NEGF simulations for the first time. Similarly, new ab initio NEGF simulations of the novel post-CMOS Au metal-channel FET are presented along side fabrication experiments towards testing simulation accuracy.\nAb initio NEGF simulations predict short channel effects to be suppressed down to LG=2nm, TSi=1.2nm, with improved ION by 80% and gm by 308% to compared to 24nm UTBB-FDSOI MOSFET measurements. Semi-classical simulations predict improvements of 46% in gm and 75% in fT for scaling down to LG=9.7nm, TSi=3.1nm.\nThe Au METFET shows no significant ION/IOFF with results being sensitive to simulation model choice. A complete METFET fabrication process flow is presented to test simulation accuracy and the smallest metal channel width ever fabricated using EBL at the University of Toronto is demonstrated at 9nm.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
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)0.0010.000

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 head0.010
GPT teacher head0.225
Teacher spread0.215 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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