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Record W1963939078 · doi:10.1117/12.661119

Metrology (including materials characterization) for nanoelectronics

2006· article· en· W1963939078 on OpenAlexaff
Alain C. Diebold, Jimmy Price, Ping-Fang Hung

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsSemtech (Canada)
FundersAssociation of Medical Research Charities
KeywordsNanoelectronicsMetrologyTransistorCMOSCharacterization (materials science)ElectronicsNanotechnologyPaceIntegrated circuitElectrical engineeringElectronic circuitEngineering physicsEngineeringComputer scienceMaterials sciencePhysicsVoltage

Abstract

fetched live from OpenAlex

Integrated circuits have already entered the world of nanoelectronics. According to the International Technology Roadmap for Semiconductors, the industry will be extending CMOS technology through new materials and device structures for at least the next fifteen years. During that time, the gate length of nanotransistors will shrink to less than 10 nm. The electrical properties of nano-transistors will move into regime of short channel devices where new physics will result in changes in transistor operation. The number of transistors in a single IC is already approaching a number that results 2 billion functions per IC by 2010. Nano-sized features and high density will challenge metrology and characterization and most certainly move measurement further into the world of nanotechnology. Beyond CMOS, new nano-technology based devices are being considered as a means of continuing the rapid pace of technological innovation in electronics.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.013
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.003
Scholarly communication0.0030.004
Open science0.0020.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0130.015

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 head0.012
GPT teacher head0.221
Teacher spread0.209 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations1
Published2006
Admission routes1
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicSemiconductor materials and devicesFrench-language works237,207