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Highly stable resistive switching on monocrystalline ZnO

2010· article· en· W1998038097 on OpenAlexafffund
Andy Shih, Wendi Zhou, Julia Qiu, Han-Jen Yang, Shuyi Chen, Zetian Mi, I. Shih

Bibliographic record

VenueNanotechnology · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsMaterials scienceMonocrystalline siliconPlanarElectrodeResistive touchscreenAnnihilationThermalOptoelectronicsMetalThermal stabilityCondensed matter physicsSiliconThermodynamicsMetallurgyChemical engineeringElectrical engineeringPhysical chemistry

Abstract

fetched live from OpenAlex

We report on the achievement of planar memristive devices on monocrystalline ZnO substrates using Ti/Al and Pt/Au contacts with dimensions of 100 x 100 microm(2) and spacings of approximately 60 microm. Effects of both thermal and electro-forming processes on the switching characteristics are investigated. It is observed that the thermally formed devices exhibit an extremely large R(OFF)/R(ON) value of approximately 20 000. The electrically formed devices, on the other hand, demonstrate an exceptional switching stability, with R(OFF)/R(ON) variations of < 2% for durations of over 10(5) s and more than 1800 switching cycles. The dependence of the switching characteristics on the formation processes, as well as the metal electrodes, could be explained by an oxygen vacancy formation/annihilation and migration model.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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 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

Citations65
Published2010
Admission routes2
Has abstractyes

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