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Research on Fabrication and Electronic Characteristics of Dual-Extended Nano Structure Memristor

2014· article· en· W1980670173 on OpenAlexaff
Xiao Hui Bai, Dian Zhong Wen, Celal Con, Mustafa Yavuz, Bo Cui

Bibliographic record

VenueKey engineering materials · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMemristorFabricationDual (grammatical number)NanostructureMaterials scienceNanotechnologyNano-Nanoscopic scaleElectrodeOptoelectronicsElectronic engineeringPhysicsEngineeringComposite material

Abstract

fetched live from OpenAlex

This paper proposes a novel dual-extended nanostructure memristor model compared to HP memristor can be called Single-extended memristor. Oxygen ions and oxygen vacancies all are effective carriers in this memristor as the structure are made of TiO 2-x /TiO 2 /TiO 2+x three nanolayers between Pt electrodes.The sample of dual-extended memristors arrays were fabricated by ways which these cost-effective methods can be exploited to produce memristors with nanoscale electrode width. Dual-extended nanostructure memristor model will be represented and the mechanism will be discussed. Fabrication methods of the memristor device are introduced and the electronic characteristics are measured and plotted. The results are discussed will experimentally demonstrated that higher switching speed and lower power will be gained by using dual-extended memristors to design IC.

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 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 score0.006
Threshold uncertainty score0.567

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)0.0000.000

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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2014
Admission routes1
Has abstractyes

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