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Record W2312305522 · doi:10.3938/jkps.57.1248

Leakage Current Characteristics of the Multiple Metal Alloy Nanodot Memory

2010· article· en· W2312305522 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of the Korean Physical Society · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsHatch (Canada)
Fundersnot available
KeywordsMaterials scienceNanodotAlloyMetalCurrent (fluid)MetallurgyOptoelectronicsElectrical engineering

Abstract

fetched live from OpenAlex

The leakage current characteristics of a multiple metal alloy nanodot device for a nonvolatile random access memory using FePt materials are investigated. Several annealing conditions are evaluated and optimized to suppress the leakage current and to better the memory characterisctics. This work confirmed that the annealing condition of 700 degrees C in a high vacuum ambience (under 1 x 10(-5) Pa) simultaneously provided good cell characteristics from a high dot density of over 1 x 10(13)/cm(2) and a low leakage current. In addition, a smaller nanodot diameter was found to give a lower leakage current for the multiple nanodot memory. Finally, for the proposed annealing condition, the quadruple FePt multiple nanodot memory with a 2-nm dot diameter provided good leakage current characteristics, showing a threshold voltage shift of under 5% at an initial retention stage of 1000 sec.

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.

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 score0.049
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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