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Record W2050182297 · doi:10.1109/jssc.2002.808289

A current-based reference-generation scheme for 1T-1C ferroelectric random-access memories

2003· article· en· W2050182297 on OpenAlexaff
J.W.K. Siu, Y. Eslami, Ali Sheikholeslami, P.G. Gulak, T. Endo, Shuichi Kawashima

Bibliographic record

VenueIEEE Journal of Solid-State Circuits · 2003
Typearticle
Languageen
FieldMaterials Science
TopicFerroelectric and Piezoelectric Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFerroelectric RAMChipSense amplifierMemory cellVoltageCurrent (fluid)Random accessScheme (mathematics)Power (physics)FerroelectricityComputer scienceElectronic engineeringAccess timeProcess (computing)Electrical engineeringMaterials scienceComputer hardwareEngineeringCapacitorPhysicsMathematicsTransistor

Abstract

fetched live from OpenAlex

A reference generation scheme is proposed for a 1T-1C ferroelectric random-access memory (FeRAM) architecture that balances fatigue evenly between memory cells and reference cells. This is achieved by including a reference cell per row (instead of per column) of the memory array. The proposed scheme converts the bitline voltage to current and compares this current against a reference current using a current-steering sense amplifier. This scheme is evaluated over a range of bitline lengths and cell sizes in a 16-Kb test chip implemented in a 0.35-μm FeRAM process. The test chip measures an access time of 62 ns at room temperature using a 3-V power supply.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.160
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.079
GPT teacher head0.337
Teacher spread0.257 · 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

Citations11
Published2003
Admission routes1
Has abstractyes

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