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Record W2314795252 · doi:10.1149/1.2209256

High-K Materials for Nonvolatile Memories

2006· article· en· W2314795252 on OpenAlexaff
Michael Specht, Martin Staedele, F. Hofmann, H. Reisinger, Michael Grieb

Bibliographic record

VenueECS Transactions · 2006
Typearticle
Languageen
FieldEngineering
TopicSemiconductor materials and devices
Canadian institutionsInfineon Technologies (Canada)
Fundersnot available
KeywordsNAND gateData retentionNon-volatile memoryHigh-κ dielectricFlash (photography)Computer scienceScalingOptoelectronicsSimplicityMaterials scienceFlash memoryElectrical engineeringDielectricComputer hardwareLogic gateEngineeringPhysics

Abstract

fetched live from OpenAlex

Nonvolatile memories based on charge storage currently dominate the high density data flash market. Multi-level floating gate in NAND array architecture as well as NROM dual bit feature lowest cost per bit and simplicity of processing and thus are likely to have largest market share. For sub 50nm flash scaling introduction of high K dielectrics will be probable. High-K materials allow for improved coupling of the word line to the floating gate still providing sufficiently large physical thickness for reliable retention properties. In this article we review the opportunities and improvements high-K materials can offer for floating gate type devices as well as for charge trapping devices such as SONOS and NROM.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
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 head0.007
GPT teacher head0.195
Teacher spread0.188 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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