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Record W4387610460 · doi:10.1063/5.0169682

Low-temperature enhanced OFF-state telegraph noise in defect engineered ReRAMs

2023· article· en· W4387610460 on OpenAlex
H. S. Alagoz, M. Egilmez, Jongwan Jung, K. H. Chow

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAPL Materials · 2023
Typearticle
Languageen
FieldEngineering
TopicAdvanced Memory and Neural Computing
Canadian institutionsUniversity of Alberta
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaAmerican University of Sharjah
KeywordsMaterials scienceNoise (video)TrappingStackingCondensed matter physicsAmplitudeResistive touchscreenOptoelectronicsResistive random-access memoryVoltageNuclear magnetic resonanceElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

The OFF-state retention characteristics of Pt/NiOx–(Ar)/NiOx–(Ar + O2)/Pt stacking resistive random access memory structures were measured as a function of temperature between 300 and 190 K. The devices show random telegraph noise effects whose noise amplitude increases upon lowering the temperature. Interestingly, the application of forward and reverse biases produces up and downresistance jumps. These results present important insights into the thermally activated charge trapping/de-trapping phenomenon that is responsible for resistance fluctuations.

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 score0.023
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
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