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Record W1590842594 · doi:10.1109/iedm.2002.1175825

FinFET scaling to 10 nm gate length

2003· article· en· W1590842594 on OpenAlex

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsTransconductanceMaterials scienceCMOSMOSFETOptoelectronicsPlanarShort-channel effectFabricationTransistorChannel (broadcasting)Design for manufacturabilityLogic gateScalingElectrical engineeringComputer scienceEngineering

Abstract

fetched live from OpenAlex

While the selection of new "backbone" device structure in the era of post-planar CMOS is open to a few candidates, FinFET and its variants show great potential in scalability and manufacturability for nanoscale CMOS. In this paper we report the design, fabrication, performance, and integration issues of double-gate FinFETs with the physical gate length being aggressively shrunk down to 10 nm and the fin width down to 12 nm. These MOSFETs are believed to be the smallest double-gate transistors ever fabricated. Excellent short-channel performance is observed in devices with a wide range of gate lengths (10/spl sim/105 nm). The observed short-channel behavior outperforms any reported single-gate silicon MOSFETs. Due to the [110] channel crystal orientation, hole mobility in the fabricated p-channel FinFET exceeds greatly that in a traditional planar MOSFET. At 105 nm gate length, the p-channel FinFET shows a record-high transconductance of 633 /spl mu/S//spl mu/m at a V/sub dd/ of 1.2 V. Working CMOS FinFET inverters are also demonstrated.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.850
Threshold uncertainty score0.998

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)0.0030.001

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 head0.015
GPT teacher head0.222
Teacher spread0.208 · 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