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Record W2042543670 · doi:10.1142/s0129156407004679

QUANTUM SIMULATIONS OF DUAL GATE MOSFET DEVICES: BUILDING AND DEPLOYING COMMUNITY NANOTECHNOLOGY SOFTWARE TOOLS ON NANOHUB.ORG

2007· article· en· W2042543670 on OpenAlex
Shaikh Ahmed, Gerhard Klimeck, Derrick Kearney, Michael McLennan, M. P. Anantram

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of High Speed Electronics and Systems · 2007
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsNanoelectronicsMOSFETSuiteSoftwareQuantum computerComputer scienceSoftware suiteElectronic engineeringCMOSQuantumNanotechnologyEngineeringElectrical engineeringPhysicsMaterials scienceTransistor

Abstract

fetched live from OpenAlex

Undesirable short-channel effects associated with the relentless downscaling of conventional CMOS devices have led to the emergence of new classes of MOSFETs. This has led to new and unprecedented challenges in computational nanoelectronics. The device sizes have already reached the level of tens of nanometers where quantum nature of charge-carriers dominates the device operation and performance. The goal of this paper is to describe an on-going initiative on nanoHUB.org to provide new models, algorithms, approaches, and a comprehensive suite of freely-available web-based simulation tools for nanoscale devices with capabilities not yet available commercially. Three software packages nanoFET, nanoMOS and QuaMC are benchmarked in the simulation of a widely-studied high-performance novel MOSFET device. The impact of quantum mechanical effects on the device properties is elucidated and key design issues are suggested.

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.

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 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 score0.096
Threshold uncertainty score0.454

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.028
GPT teacher head0.277
Teacher spread0.250 · 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